Top AI Data Engineer Jobs Openings in 2025

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Ironclad is the leading AI-powered contract lifecycle management platform, processing billions of contracts every year. Every business is powered by contracts, but managing them can slow companies down and cost millions of dollars. Global innovators like L’Oréal, OpenAI, and Salesforce trust Ironclad to transform contracting into a strategic advantage - accelerating revenue, reducing risk, and driving efficiency. It’s the only platform that manages every type of contract workflow, whether a sales agreement, an HR agreement or a complex NDA. We’re building the future of intelligent contracting and writing the narrative for how contracts unlock strategic growth. Forrester Wave and Gartner Magic Quadrant have consistently recognized Ironclad as a leader in our category. We’ve also been named one of Fortune’s Great Places to Work six years running, featured on Glassdoor’s Best Places to Work, and recognized by Forbes’ 50 Most Promising AI Companies. We’re backed by leading investors like Accel, Sequoia, Y Combinator, and BOND. We’d love for you to join us! This is a hybrid role. Office attendance is required at least twice a week on Tuesdays and Thursdays for collaboration and connection. There may be additional in-office days for team or company events. About Ironclad ITOur IT team plays a pivotal role in creating platforms for success so our Ironclad team can execute on our vision. As an IT teammate, you’ll partner with our Operations team on growth strategies and execute on technology needs as we grow. You also bring empathy to understand employee technology needs. You’ll enable the team, build out new offices, and design IT strategy for a fast-paced, fast-growing technology company.Roles & Responsibilities:Lead, mentor, and manage a team of data engineers, fostering a culture of collaboration, innovation, and continuous improvement.Collaborate with other technical and non-technical teams to understand business requirements and translate them into efficient data engineering solutions.Design, implement, and maintain data pipelines and ETL processes that support data integration, transformation, and loading into the data warehouse.Ensure data quality, reliability, and consistency by implementing robust testing, monitoring, and validation processes.Stay current with industry trends and best practices in data engineering, cloud technologies, and data architecture.Drive the adoption of best practices for data governance, data security, and compliance within the data engineering team.Manage project timelines, resource allocation, and priorities to ensure timely delivery of data engineering projects.Collaborate with other directors and leaders to align data engineering initiatives with broader business objectives.Work closely with the IT & Security DS and other cross-functional DS teams on design, reference architecture, and Data Strategy.Experience setting journey driven by enterprise business outcomes, modernization, and stakeholder alignment.Excellent communication skills with technical and non‑technical audiences.Aptitude for budgeting, vendor negotiation, and operational efficiency.Qualifications:Strong data infrastructure and data architecture skills.A proven track record of leading and scaling large data teams.Strong operational skills to drive efficiency and speed.Strong project management leadership.Strong vision for how Data Engineering can proactively improve companies.12+ years of experience in Analytics, BI, and Data Warehousing.Experience scaling and managing 20+ person teams and in managing managers.Experience leading in a highly cross-functional environment, likely collaborating closely with Engineering, Product Management, and/or Data Science.Communication and leadership experience, with experience initiating and driving large-scale strategic initiatives.Data architecture experience.Experience in SQL or similar languages.Development experience in at least one object-oriented language (Python, Java, etc.).Solid understanding of how experimentation (A/B testing) works.Requirements:Bachelor's or Master's degree in Computer Science, Engineering, or a related field.Proven experience (8+ years) in data engineering, with at least 5 years in a senior leadership role.Strong hands-on experience with cloud-based data engineering platforms preferred (e.g. GCP, Google Big Query, Looker, Databricks, Snowflake, dbt Labs, Airflow, Fivetran).Proficiency in SQL, Python, and other relevant programming languages.Experience with data modeling, ETL processes, and data integration patterns.Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.Strong leadership and team management skills, with the ability to inspire and develop a high-performing team.Familiarity with agile development methodologies and project management practices.Adept at problem-solving, critical thinking, and decision-making in a fast-paced environment.Practical experience with data governance and compliance frameworks.Hands-on proficiency with data streaming and real-time data processing technologies.Benefits:Health, dental, and vision insurance401kWellness reimbursementTake what you need vacation policyGenerous parental leave for both primary and secondary caregiversBase Salary Range: $265,000 - $294,000The base salary range represents the minimum and maximum of the salary range for this position based at our San Francisco headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of Ironclad’s competitive total rewards package, which also includes equity awards (a new hire grant, along with opportunities for additional awards throughout your tenure), competitive health and wellness benefits, and a commitment to career growth and development.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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Introduction to Demandbase:  Demandbase is the leading account-based GTM platform for B2B enterprises to identify and target the right customers, at the right time, with the right message. With a unified view of intent data, AI-powered insights, and prescriptive actions, go-to-market teams can seamlessly align and execute with confidence. Thousands of businesses depend on Demandbase to maximize revenue, minimize waste, and consolidate their data and technology stacks - all in one platform. As a company, we’re as committed to growing careers as we are to building world-class technology. We invest heavily in people, our culture, and the community around us. We have offices in the San Francisco Bay Area, Seattle, and India, as well as a team in the UK, and allow employees to work remotely. We have also been continuously recognized as one of the best places to work in the San Francisco Bay Area including, “Best Workplaces for Millennials” and “Best Workplaces for Parents”! We're committed to attracting, developing, retaining, and promoting a diverse workforce. By ensuring that every Demandbase employee is able to bring a diversity of talents to work, we're increasingly capable of living out our mission to transform how B2B goes to market. We encourage people from historically underrepresented backgrounds and all walks of life to apply. Come grow with us at Demandbase! The base compensation range for this position for candidates in the SF Bay Area is: $165,000 - $284,000. For all other locations, the base compensation range is based on the primary work location of the candidate as our ranges are location specific. Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skillset, years of experience, and depth of experience. About the Role: As a Senior Data Engineer, you will play a pivotal role in architecting and scaling our data platforms, building robust and scalable data pipelines, and enabling data-driven decision-making across the company. You’ll work with massive, complex datasets from a variety of third-party and internal sources — driving data infrastructure and platform evolution to support both real-time and batch processing needs. In this role, you’ll not only write code but also influence the data strategy, mentor junior engineers, and collaborate cross-functionally with product, analytics, and platform teams.  This role supports our Intent product where you will improve the core pipelines as well as design new processes that enable our data science team to test and deploy new ML/AI models. The product delivered by this team is integrated into the core product stack and is a critical component of Demandbase’s account intelligence platform. This is a high-impact individual contributor role for someone who combines deep technical knowledge with strategic thinking and a bias for action. What You’ll Be Doing: Design & Architect: Lead the end-to-end design and evolution of scalable, resilient data pipelines and infrastructure, driving architecture decisions that impact the company’s data platform long-term. Build & Scale: Develop and optimize large-scale data processing workflows (batch and streaming), using Spark and related technologies, ingesting data from diverse internal and external sources. Mentor & Lead: Provide technical leadership and mentorship to mid- and junior-level engineers. Review design docs, PRs, and contribute to engineering best practices across the team. Improve Reliability: Build fault-tolerant, observable systems with self-healing and robust monitoring using tools like Airflow, Datadog, or equivalent. Collaborate: Partner with cross-functional stakeholders in Product, Analytics, and Infrastructure to ensure data architecture aligns with business needs and SLAs. Own & Operate: Take full lifecycle ownership of key data pipelines and integrations—from design to deployment to production support. What we’re looking for: Bachelor’s degree in computer science, engineering, mathematics, or related field 7+ years of experience in software/data engineering roles, with deep expertise in building and maintaining large-scale distributed data systems. Scala experience required. Comfort with purely functional programming is a plus. Strong CS fundamentals, including algorithms, data structures, and system design. Strong background in data modeling, performance tuning, and data integration best practices. Experience owning end-to-end systems, including production monitoring, incident response, and system reliability engineering. Proficiency in cloud-native data platforms (e.g., GCP or AWS), including managed services for analytics and orchestration. Familiarity with real-time data processing, streaming architectures, and event-driven design. Excellent verbal and written communication skills; comfortable explaining complex concepts to technical and non-technical stakeholders. A strong sense of ownership, initiative, and accountability. BS or MS in Computer Science required Benefits: We offer a comprehensive benefits package designed to support your health, well-being, and financial security. Our employees enjoy up to 100% paid premiums for Medical and Vision coverage, ensuring access to top-tier care for you and your loved ones. In addition, we provide a range of mental wellness resources, including access to Modern Health, to help support your emotional well-being. We believe in a healthy work-life harmony, which is why we offer a flexible PTO policy, 15 paid holidays in 2025—including a three-day break around July 4th and a full week off for Thanksgiving—and No Internal Meetings Fridays to give you uninterrupted time to focus on what matters most. For your financial future, we offer a competitive 401(k) plan, short-term and long-term disability coverage, life insurance, and other valuable benefits to ensure your financial peace of mind. Our Commitment to Diversity, Equity, and Inclusion at Demandbase: At Demandbase, we believe in creating a workplace culture that values and celebrates diversity in all its forms. We recognize that everyone brings unique experiences, perspectives, and identities to the table, and we are committed to building a community where everyone feels valued, respected, and supported. Discrimination of any kind is not tolerated, and we strive to ensure that every individual has an equal opportunity to succeed and grow, regardless of their gender identity, sexual orientation, disability, race, ethnicity, background, marital status, genetic information, education level, veteran status, national origin, or any other protected status. We do not automatically disqualify applicants with criminal records and will consider each applicant on a case-by-case basis. We recognize that not all candidates will have every skill or qualification listed in this job description. If you feel you have the level of experience to be successful in the role, we encourage you to apply! We acknowledge that true diversity and inclusion requires ongoing effort, and we are committed to doing the work required to make our workplace a safe and equitable space for all. Join us in building a community where we can learn from each other, celebrate our differences, and work together.      Personal information that you submit will be used by Demandbase for recruiting and other business purposes. Our Privacy Policy explains how we collect and use personal information.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleIf you’re a professional who works with AI Data Annotation and friendly user of LLMs, Mindrift offers a unique opportunity to apply your editing, annotating, fact-checking and creative skills to an AI training project.This is a freelance role for a project, and your typical tasks may include: Conduct high-quality web searches to verify facts, gather supporting data, and cross-check AI responses. Perform fact-checking and intent verification to ensure AI responses align with the user's goals. Carefully review and flag any inaccuracies, inconsistencies, or irrelevant answers. Provide structured feedback on AI-generated content to help improve model performance. Work effectively with large language models (LLMs), understanding their capabilities and limitations, and applying best practices when interacting with them. Prompt generation with a purpose to receive the best quality result of LLMs. How to get startedSimply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.Requirements You are currently enrolled in or completed a Bachelor's degree or higher. You have professional and/or educational experience in data annotation, demonstrate a deeper-than-user-level interest in AI, and possess intellectual breadth and curiosity. You are skilled in web searching, fact-checking, intent-checking, able to work with LLMs and have great attention to detail. Your level of English is upper-intermediate (B2) or above. You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines. Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge. BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments. Work on advanced AI projects and gain valuable experience that enhances your portfolio. Influence how future AI models understand and communicate in your field of expertise.

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About SignalFireSignalFire is the first VC firm built like a technology company to better serve the needs of founders as they build and scale their startups. With approximately $3B in assets under management, SignalFire invests in applied AI companies from pre-seed to Series B in key sectors, including healthcare, cybersecurity, infrastructure, consumer, and other enterprise verticals.The firm’s Beacon AI platform tracks over 650M employees and 80M organizations, giving the firm an unmatched data advantage in identifying and supporting world-class startups. Its sector-focused investors and a dedicated team of seasoned operators drive SignalFire at startup speed. They provide support across a company’s full lifecycle through data and resources tailored by growth stage, plus a diverse ecosystem of partners and customers. Notable investments include Frame.io, Grammarly, Grow Therapy, EvenUp, and Stampli.Learn more at www.signalfire.comRole DescriptionSignalfire is looking for an exceptional engineer who is passionate about building robust data infrastructure that powers complex analytical workflows, machine learning processes, and data-intensive web application. As our data engineer, you will work closely with our investment, portfolio, talent team, and the rest of our engineering organization to build best-in-class tools that help us explore potential investment areas and support our portfolio companies.What you’ll be doing:Building industry-standard backend architecture and data pipelines for our AI platform, Beacon which helps our firm invest in the best startups in the marketProcuring and evaluating potential new data sources in service of identifying, diligencing, and supporting startupsBuild and maintain scalable, maintainable data transformation pipelines using Python, Spark, dbt, apache/airflow to power the whole company's data science and analytics needsStand up new low-latency data processing infrastructure to provide clean data to machine learning modelsImprove workflow orchestration and automation processes for existing systemsYour background:2 to 6 years of experience working as a data engineerA solid conceptual grasp (and preferably hands-on experience with) orchestration frameworks like Airflow, Dagster, Prefect, or similarExperience with ETL, data processing, pipelining, and sanitizingExperience working on complex data pipelines using SQL, Redshift, Python, dbtExperience building backend infrastructure and architecture required to power frontend featuresUnderstanding of data modeling strategies for both transactional and data warehousing workloadsExceptional problem solving, analysis, decomposition, and communication skills applied within an agile development environmentBS/MS in statistics, computer science, economics, or a similarly quantitative fieldTakes pride working on large projects from scratch to completionSan Francisco Bay Area or New York basedWhy SignalFire?In addition to working directly with our team at the forefront of a hybrid human + technology investment approach, you’ll also work closely with founders to help them solve major problems.Our culture is one that breeds creativity and impact and puts you in control of your own destiny.End-to-end ownership: Engineers at SignalFire own the full stack—from data acquisition and model development to infrastructure and product delivery. This extends beyond code; you'll work directly with the investment team, gaining insight into how your work shapes strategic decisions.Empowered decision-making: We’ve cut the bureaucracy of big companies but kept their resources. Have a strong idea? Pitch it. You’ll get budget and ownership. We move like a startup but execute with the discipline of a mature company.Versatile technical expertise: We value engineers who blend startup agility with enterprise depth. You'll wear many hats—tuning infrastructure one day, refining algorithms or designing features the next—building a skillset rarely found elsewhere.Creative autonomy: At SignalFire, creativity isn’t just valued—it’s essential. We tackle problems without clear precedents, where sharp judgment and innovation matter more than technical orthodoxy. Success means balancing analytical rigor with a bias to ship, learn, and iterate.You can read more about life on the engineering team here: https://www.signalfire.com/blog/engineering-at-the-heart-of-venture-capitalCompensationUSD 170k-270k base salary/year based on experience + Carried InterestDoes this sound like you? If so, we'd love to hear from you!

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About KreaAt Krea, we are building next-generation AI creative tools.We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that empower human creativity, not replace it.We believe AI is a new medium that allows us to express ourselves through various formats—text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium. This jobData is one of the fundamental pieces of Krea. Huge amounts of data power our AI training pipelines, our analytics and observability, and many of the core systems that make Krea tick.As a data engineer, you will…… build distributed systems to process gigantic (petabytes) amounts of files of all kinds (images, video, and even 3D data). You should feel comfortable solving scaling problems as you go.… work closely with our research team to build ML pipelines and deploy models to make sense of raw data.… play with massive amounts of compute on huge kubernetes GPU clusters - our main GPU cluster takes up an entire datacenter from our provider.… learn machine learning engineering (ML experience is a bonus, but you can also learn it on the job) from world-class researchers on a small yet highly effective tight-knit team.Example projectsFind clean scenes in millions of videos, running distributed data pipelines that detect shot boundaries and saving timestamps of clips.Solve orchestration and scaling issues with a large-scale distributed GPU job processing system on kubernetess.Build systems to deploy and combine different LLMs to caption massive amounts of multimedia data in a variety of different ways.Design multi-stage pipelines to turn petabytes of raw data into clean downstream datasets, with metadata, annotations, and filters.Strong candidates may have experience with…Python, PyArrow, DuckDB, SQL, massive relational databases, PyTorch, Pandas, NumPy…KubernetesDesigning and implementing large-scale ETL systemsFundamental knowledge of containerization, operating systems, file-systems, and networking.Distributed systems designAbout usWe’re building AI creative tooling.We’ve raised over $83M from the best investors in Silicon Valley.We’re a team of 12 with millions of active users scaling aggressively.

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Join Our Mission to Revolutionize Healthcare Thoughtful is pioneering a new approach to automation for all healthcare providers! Our AI-powered Revenue Cycle Automation platform enables the healthcare industry to automate and improve its core business operations. We're looking for Staff Data Engineers to help scale and strengthen our data platform. Our data stack today consists of Aurora RDS, AWS Glue, Apache Iceberg, S3 (Parquet), Spark and Athena - supporting a range of use cases from operational reporting to downstream services. We’re looking to grow the team with engineers who can help improve performance, increase reliability, and expand the platform's capabilities as our data volume and complexity continue to grow. You’ll work closely with other engineers to evolve our existing pipelines, improve observability and data quality, and enable faster, more flexible access to data across the company. The platform is deployed on AWS using OpenTofu, and we’re looking for engineers who bring strong cloud infrastructure fundamentals alongside deep experience in data engineering. Your Role: Build: Develop and maintain data pipelines and transformations across the stack. Starting from ingesting transactional data into the data lakehouse to refining data up the medallion data architecture. Optimize: Tune performance, storage layout, and cost-efficiency across our data storage and query engines. Extend: Help design and implement new data ingestion patterns and improve platform observability and reliability. Collaborate: Partner with engineering, product, and operations teams to deliver well-structured, trustworthy data for diverse use cases. Contribute: Help establish and evolve best practices for our data infrastructure, from pipeline design to OpenTofu-managed resource provisioning. ​​Secure: Help design and implement a data governance strategy to secure our data lakehouse. Your Qualifications: 8-10+ years of experience building and maintaining data pipelines in production environments Strong knowledge of the data lakehouse ecosystem, with an emphasis on AWS data services - particularly Glue, S3, Athena/Trino/PrestoDB, and Aurora Proficiency in Python, Spark and Athena/Trino/PrestoDB for data transformation and orchestration Experience managing infrastructure with OpenTofu/Terraform or other Infrastructure-as-Code tools Solid understanding of data modeling, partitioning strategies, schema evolution, and performance tuning Comfortable working with cloud-native data pipelines and batch processing (streaming experience is a plus but not required) What Sets You Apart: Systems thinker - you understand the tradeoffs in data architecture and design for long-term stability and clarity Outcome-driven - you focus on building useful, maintainable systems that serve real business needs Strong collaborator - you're comfortable working across teams and surfacing data requirements early Practical and hands-on - able to dive into logs, schemas, and IAM policies when needed Thoughtful contributor - committed to improving code quality, developer experience, and documentation across the board Why Thoughtful? Competitive compensation Equity participation: Employee Stock Options. Health benefits: Comprehensive medical, dental, and vision insurance. Time off: Generous leave policies and paid company holidays. California Salary Range $190,000—$250,000 USD

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About the Team:OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Data Center Engineering team is at the core of this mission. This team sets the infrastructure strategy, develops cutting-edge engineering solutions, partners with research teams to define the infrastructure performance requirements, and creates reference designs to enable rapid global expansion in collaboration with our partners. As a key member of this team, you will help design and deliver next-generation power, cooling, and hardware solutions for high-density rack deployments in some of the largest data centers in the world. You will work closely with stakeholders across research, site selection, design, construction, commissioning, hardware engineering, deployment, operations, and global partners to bring OpenAI’s infrastructure vision to life.About the Role:We’re seeking a seasoned data center R&D engineer with extensive experience in designing, performing validation testing, commissioning, and operating large-scale power, cooling, and high-performance computing systems. This role focuses on developing and validating new infrastructure and hardware, including high-voltage rectifiers, UPS systems, battery storage, transformers, DC to DC converters, and power supplies. The role will lead the design and buildout of a hardware validation lab, create detailed models and test procedures, and ensure hardware compatibility across edge-case data center operating conditions. Additionally, the role involves working closely with hardware vendors to assess manufacturing test protocols, throughput, and liquid-cooled GPU rack performance. A strong foundation in technical design, operational leadership, and vendor collaboration is critical, with an opportunity to lead high-impact infrastructure programs.You Might Thrive in this Role:Oversee electrical, mechanical, controls, and telemetry design and operations for large-scale data centers, including review of building and MEP drawings across all project phases from concept design to permitting, construction, commissioning and production.Develop, test and implement operational procedures and workflows from design through commissioning and deployment.Perform validation testing of all critical equipment and hardware in partnership with equipment vendors and ODMs.Lead buildout of R&D lab, including equipment selection, test infrastructure for high-density liquid-cooled racks, and staffing plans.Select and manage engineering tools (CAD, CFD, PLM, PDM, electrical, mechanical, power/network management).Collaborate with external vendors to select, procure, and manage critical infrastructure equipment (e.g., UPS, generators, transformers, DC to DC converters, chillers, VFDs).Ensure seamless integration of power, cooling, controls, networking, and construction systems into facility design.Provide technical direction to teams and vendors, ensuring safety, quality, and compliance with local codes, standards and regulations.Manage vendor relationships and ensure adherence to safety, performance, and operational standards.Qualifications:20+ years of experience in data center design, operations, and critical systems maintenance.Proven leadership across design, commissioning, and operation of large-scale data center campuses.Deep expertise in infrastructure systems (power, cooling, controls, networking) and operational workflows.Hands-on experience with critical infrastructure equipment and testing protocols.Strong track record in lab development, equipment selection, and facility operations.Familiarity with engineering tools (CAD, CFD, PLM, etc.) and their integration across teams.Experience navigating regulatory environments and working with government agencies.Excellent cross-functional communication and stakeholder collaboration.Bachelor’s degree in engineering required; advanced degree and PE certification preferred.Preferred Skills:Expertise in equipment design, agency certification, and validation testing.Experience in global, matrixed organizations and multi-site operations.Skilled in vendor negotiations and supply chain management.Familiarity with sustainable and energy-efficient data center design principles.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About Glean: Founded in 2019, Glean is an innovative AI-powered knowledge management platform designed to help organizations quickly find, organize, and share information across their teams. By integrating seamlessly with tools like Google Drive, Slack, and Microsoft Teams, Glean ensures employees can access the right knowledge at the right time, boosting productivity and collaboration. The company’s cutting-edge AI technology simplifies knowledge discovery, making it faster and more efficient for teams to leverage their collective intelligence. Glean was born from Founder & CEO Arvind Jain’s deep understanding of the challenges employees face in finding and understanding information at work. Seeing firsthand how fragmented knowledge and sprawling SaaS tools made it difficult to stay productive, he set out to build a better way - an AI-powered enterprise search platform that helps people quickly and intuitively access the information they need. Since then, Glean has evolved into the leading Work AI platform, combining enterprise-grade search, an AI assistant, and powerful application- and agent-building capabilities to fundamentally redefine how employees work.About the Role: Glean is building a world-class Data Organization composed of data science, applied science, data engineering and business intelligence groups. Our data engineering group is based in our Bangalore, India office. In this role, you will work on customer-facing and Glean employee-facing analytics initiatives: Customer-facing analytics initiatives: Customers rely on in-product dashboards and if they have the willingness and resources, self-serve data analytics to understand how Glean’s being used at their company in order to get a better sense of Glean’s ROI and partner with Glean to increase user adoption.  You’re expected to partner with backend and data science to maintain and improve the data platform behind these operations reflect usage on new features reflect changes on the underlying product usage logs on existing features identify and close data quality issues, e.g. gaps with internal tracking, and backfill the changes triage issues customers report to us within appropriate SLAs help close customer-facing technical documentation gaps  You will: Help improve the availability of high-value upstream raw data by  channeling inputs from data science and business intelligence to identify biggest gaps in data foundations partnering with Go-to-Market & Finance operations groups to create streamlined data management processes in enterprise apps like Salesforce, Marketo and various accounting software partnering with Product Engineering teams as they craft product logging initiatives & processes Architect and implement key tables that transform structured and unstructured data into usable models by the data, operations, and engineering orgs. Ensure and maintain the quality and availability of internally used tables within reasonable SLAs Own and improve the reliability, efficiency and scalability of ETL tooling, including but not limited to dbt, BigQuery, Sigma. This includes identifying implementing and disseminating best practices as well. About you: You have 9+ yrs of work experience in software/data engineering (former is strongly preferred) as a bachelor degree holder. This requirement is 7+ for masters degree holders and 5+ for PhD Degree holders. You’ve served as a tech lead and mentored several data engineers before. Customer-facing analytics initiatives: You have experience in architecting, implementing and maintaining robust data platform solutions for external-facing data products. You have experience with implementing and maintaining large-scale data processing tools like Beam and Spark. You have experience working with stakeholders and peers from different time zones and roles, e.g. ENG, PM, data science, GTM, often as the main data engineering point of contact. Internal-facing analytics initiatives: You have experience in full-cycle data warehousing projects, including requirements analysis, proof-of-concepts, design, development, testing, and implementation You have experience in database designing, architecture, and cost-efficient scaling You have experience with cloud-based data tools like BigQuery and dbt You have experience with data pipelining tools like Airbyte, Apache, Stitch, Hevo Data, and Fivetran General qualifications: You have a high degree of proficiency with SQL and are able to set best practices and up-level our growing SQL user base within the organization You are proficient in at least one of Python, Java and Golang. You are familiar with cloud computing services like GCP and/or AWS. You are concise and precise in written and verbal communication. Technical documentation is your strong suit.  You are a particularly good fit if: You have 1+ years of tech lead management experience. Note this is distinct from having a tech lead experience, and involves formally managing others. You have experience working with customers directly in a B2B setting. You have experience with Salesforce, Marketo, and Google Analytics. You have experience in distributed data processing & storage, e.g. HDFS Location: This role is hybrid (3 days a week in our Bangalore office) We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.

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About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About the role As an early member of our Finance Analytics and Business Intelligence team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by establishing robust analytics engineering and business intelligence capabilities for our Finance & Strategy (F&S) organization. In this unique company, technology, and moment in history, your work will be critical to ensuring accurate financial reporting, streamlining F&S processes, and developing data products as we deploy safe, frontier AI at scale to the world.  In this experienced individual contributor role as the first team member focused on analytics engineering for Finance & Strategy, you will use advanced analytics to drive strategic decision-making. Using your generalist analytics engineering skillset, you'll work at the intersection of finance, analytics, and business intelligence to develop automated reporting systems, data quality frameworks, and scaled insights that support our various business models and entities. You’ll partner closely across Data Infrastructure, Data Science & Analytics, Finance Systems, and Finance & Strategy. You've worked in cultures of excellence in the past and are eager to apply that experience to building robust, scalable systems and processes as our company goes through a phase of rapid growth. Responsibilities: Evolve analytics engineering and BI for Finance & Strategy at Anthropic, creating processes and best practices for financial data management, governance, and reporting Build and maintain canonical datasets, dashboards, and scaled insights solutions that provide real-time insights to finance and executive leadership Partner with Finance & Strategy teams (Product, Compute, GTM, and Corporate) to streamline recurring processes and increase velocity for analytical deep dives Partner with Data Infrastructure, Analytics Engineering, and Financial Systems teams to develop scalable data pipelines and infrastructure supporting accounting analytics Champion data-informed decision making across the organization You may be a good fit if you: Have 6+ years of hands-on experience in finance analytics, business intelligence, or analytics engineering with demonstrated experience partnering directly with Finance & Strategy, Data Infrastructure, and Financial Systems teams Are highly proficient in SQL and Python for data manipulation, ETL/ELT processes, analysis, and automation Have extensive experience with BI visualization tools such as Looker, Tableau Have experience with cloud platforms (AWS, GCP), modern data stack tools (dbt, Airflow, etc.) Have hands-on experience working with financial systems like NetSuite, Stripe, or other ERP/financial platforms, and building downstream data models from these systems Excel at translating complex business requirements into technical solutions and can communicate effectively with both technical and non-technical stakeholders Are detail-oriented with a commitment to data accuracy and have experience building robust, scalable analytical solutions Thrive in fast-paced environments and can manage multiple priorities while maintaining high-quality deliverables Strong candidates may have: Relevant certifications in financial systems or business intelligence platforms Prior experience in high-growth technology companies or startups Knowledge of statistical analysis and advanced analytics techniques Experience with financial planning and analysis (FP&A) processes and systems Strong financial acumen with deep understanding of finance principles (GAAP vs. non-GAAP, revenue recognition), financial statements, and corporate finance processes Familiarity with data governance best practices and experience implementing data quality frameworks  The expected salary range for this position is:Annual Salary:$265,000—$315,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process

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At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.So, what’s the role all about? We are seeking a skilled Senior Data Engineer to join our Actimize Watch Data Analytics team. In this role, you will collaborate closely with the Data Science team, Business Analysts, SMEs to monitor and optimize the performance of machine learning models. You will be responsible for running various analytics on data stored in S3, using advanced Python techniques, generating performance reports & visualization in Excel, and showcasing model performance & stability metrics through BI tools such as Power BI and Quick Sight. How will you make an impact? Data Integration and Management: Design, develop, and maintain robust Python scripts to support analytics and machine learning model monitoring. Ensure data integrity and quality across various data sources, primarily focusing on data stored in AWS S3. Check the data integrity & correctness of various new customers getting onboarded to Actimize Watch   Analytics and Reporting: Work closely with Data Scientists, BAs & SMEs to understand model requirements and monitoring needs. Perform complex data analysis as well as visualization using Jupyter Notebooks, leveraging advanced Python libraries and techniques. Generate comprehensive model performance & stability reports, showcase them in BI tools. Standardize diverse analytics processes through automation and innovative approaches.   Model Performance Monitoring: Implement monitoring solutions to track the performance and drift of machine learning models in production for various clients. Analyze model performance over time and identify potential issues or areas for improvement. Develop automated alerts and dashboards to provide real-time insights into model health.   Business Intelligence and Visualization: Create and maintain dashboards in BI tools like Tableau, Power BI and QuickSight to visualize model performance metrics. Collaborate with stakeholders to ensure the dashboards meet business needs and provide actionable insights. Continuously improve visualization techniques to enhance the clarity and usability of the reports.   Collaboration and Communication: Work closely with cross-functional teams, including Data Scientists, Product Managers, Business Analysts and SMEs  to understand requirements and deliver solutions. Communicate findings and insights effectively to both technical and non-technical stakeholders. Provide support and training to team members on data engineering and analytics best practices and tools. Have you got what it takes?  5 to 7 years of experience in data engineering, with a focus on analytics, data science and machine learning model monitoring. Proficiency in Python and experience with Jupyter Notebooks for data analysis. Strong experience with AWS services, particularly S3 and related data processing tools. Expertise in Excel for reporting and data manipulation. Hands-on experience with BI tools such as Tableau, Power BI and QuickSight. Solid understanding of machine learning concepts and model performance metrics. Strong Python & SQL skills for querying and manipulating large datasets. Excellent problem-solving and analytical skills. Ability to work in a fast-paced, collaborative environment. Strong communication skills with the ability to explain technical concepts to non-technical stakeholders. Preferred Qualifications: Experience with other AWS services like S3, Glue as well as BI tools like QuickSight & PowerBI Familiarity with CI/CD pipelines and automation tools. Knowledge of data governance and security best practices. What’s in it for you?  Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!  Enjoy NiCE-FLEX!   At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.  Requisition ID: 7900 Reporting into: Tech Manager Role Type: Individual Contributor About NiCE NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions. Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries. NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.  

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About UsMoonvalley is developing cutting-edge generative AI models designed to power Superbowl-worthy commercials and award-winning cinematic experiences. Our inaugural, cutting-edge HD model, Marey, is built on exclusively licensed and owned data for professional use in Hollywood and enterprise applications.Our team is an unprecedented convergence of talent across industries. Our elite AI scientists from Deepmind, Google, Microsoft, Meta & Snap, have decades of collective experience in machine learning and computational creativity. We have also established the first AI-enabled movie studio in Hollywood, filled with accomplished filmmakers and visionary creative talent. We work with the top producers, actors, and filmmakers in Hollywood as well as creative-driven global brands. So far we've raised over $70M from world-class investors including General Catalyst, Bessemer, Khosla Ventures & YCombinator – and we're just getting started.Role Summary:We're seeking a Head of Data to define and execute our comprehensive data strategy as we scale our next-generation generative video models. You will build and lead the data organization, ensuring Moonvalley maintains its competitive advantage through exclusive access to the highest quality, legally compliant datasets in the industry.You'll establish data governance frameworks, drive acquisition partnerships with content creators and studios, oversee compliance and licensing, and manage the complete data lifecycle powering our AI models. This role requires technical depth, strategic thinking, and executive leadership to navigate the complex landscape of data rights, quality, and scale in generative AI.What you'll do:Define and execute comprehensive data strategy, roadmap, and organizational visionBuild and scale the data team, managing data engineers, scientists, analysts, and compliance specialistsLead negotiations for large-scale data acquisition deals with studios, content creators, and media companiesEstablish data governance policies, compliance frameworks, and quality standardsOversee data infrastructure, pipelines, and processing systems architecturePartner with research, legal, and executive teams to align data initiatives with business objectivesManage data licensing, copyright compliance, and regulatory requirementsDrive innovation in data processing, curation, and quality assessment methodologiesWhat we're looking for:8+ years of data leadership experience building and scaling data organizations at high-growth technology companiesDeep experience with large-scale data infrastructure, ML pipelines, and distributed systemsProven track record developing data strategies and managing cross-functional teamsExperience with dataset licensing, intellectual property rights, and compliance frameworksUnderstanding of machine learning workflows and model training data requirementsStrong business acumen with ability to negotiate complex partnerships and contractsExceptional communication skills for executive presentations and external stakeholder managementExperience with multi-modal datasets, particularly video, and associated technical challengesNice to Haves:Experience at a generative AI company or with foundation model training datasetsBackground in media/entertainment industry with existing industry relationshipsExperience with international data regulations and cross-border complianceAdvanced degree in computer science, data science, or related technical fieldIn our team, we approach our work with the dedication similar to Olympic athletes. Anticipate occasional late nights and weekends dedicated to our mission. We understand this level of commitment may not suit everyone, and we openly communicate this expectation.If you're motivated by deeply technical problems, a seemingly never-ending uphill battle and the opportunity to build (and own) a generational technology company, we can give you what you're looking for.All business roles at Moonvalley are hybrid positions by default, with some fully remote depending on the job scope. We meet a few times every year, usually in London, UK or North America (LA, Toronto) as a company.If you're excited about the opportunity to work on cutting-edge AI technology and help shape the future of media and entertainment, we encourage you to apply. We look forward to hearing from you!The statements contained in this job description reflect general details as necessary to describe the principal functions of this job, the level of knowledge and skill typically required and the scope of responsibility. It should not be considered an all-inclusive listing of work requirements. Individuals may perform other duties as assigned, including work in other functional areas to cover absences, to equalize peak work periods, or to otherwise balance organizational workMoonvalley AI is proud to be an equal opportunity employer. We are committed to providing accommodations. If you require accommodation, we will work with you to meet your needs.Please be assured we'll treat any information you share with us with the utmost care, only use your information for recruitment purposes and will never sell it to other companies for marketing purposes. Please review our privacy policy and job applicant privacy policy located here for further information.

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EvenUp is one of the fastest-growing generative AI startups in history, on a mission to level the playing field for personal injury victims, which range from motor vehicle accidents to child abuse cases. Our products empower law firms to secure faster settlements, higher payouts, and better outcomes for those who need it most.The Analytics team at EvenUp plays a critical role in driving data-informed decision-making across the organization. We partner closely with Product, Engineering, Operations, and Executive teams to uncover insights, build scalable data solutions, and enable a culture of data-driven decision making and continuous improvement. Our team is responsible for everything from foundational data modeling and reporting to advanced analytics and forecasting. We’re looking for a Senior Data Engineer - Analytics to join our fast-paced, data-driven team. You’ll play a key role in building and scaling the data foundations that enable fast, reliable, and actionable insights. You’ll work closely with partner teams to drive end-to-end analytics initiatives and work alongside Data Scientists, ML Engineers, Product Managers, Software Engineers and Operations. Please Note: This is a hybrid role with the expectation of working at least 3 days a week from one of our office hubs in San Francisco OR Toronto, Canada. What You'll DoPartner with product, analytics, and operations teams to understand data needs and translate them into scalable models and pipelines.Build and maintain robust, well-documented ELT pipelines using tools like dbt, Airflow/Dagster, and Snowflake (or similar).Own the design and evolution of data models that support reporting, experimentation, and product feature instrumentation.Improve data quality and reliability by establishing and maintaining testing, monitoring, and alerting practices.Help drive our data architecture forward with a focus on usability, performance, strong data governance, and scalability.Mentor other engineers and analysts on data best practices, modeling standards, and tooling. What We're Looking For4+ years of experience as a Data Engineer, Analytics Engineer or Business Intelligence Engineer, ideally in product-focused, fast-paced environmentsStrong experience with designing dimensional models and defining clear source-of-truth metricsStrong proficiency in SQL for data transformation, comfort in at least one functional/OOP language such as Python or Scala for data wrangling or orchestration logicExpertise in creating compelling reporting and data visualization solutions using dashboarding tools (e.g., Looker, Tableau, Metabase)A self starter, comfort working in fast paced and evolving environments with a bias toward actionExcellent communication skills and experience collaborating closely with product managers and business stakeholdersStrong interpersonal skills, with the ability to build relationships and trust across functions and work collaborativelyStrong attention to detail, structured thinking, and experience developing processes to reduce human errorBonus PointsExperience with DBT / Bigquery / Dagster / PythonExperience working as a product software engineerExperience working in the legal domainExperience working with document processing with unstructured dataNotice to Candidates:EvenUp has been made aware of fraudulent job postings and unaffiliated third parties posing as our recruiting team – please know that we have no affiliation or connection to these situations. We only post open roles on our career page (https://jobs.ashbyhq.com/evenup) or reputable job boards like our official LinkedIn or Indeed pages, and all official EvenUp recruitment emails will come from the domains @evenuplaw.com, @evenup.ai, @ext-evenuplaw.com or no-reply@ashbyhq.com email address. If you receive communication from someone you believe is impersonating EvenUp, please report it to us by emailing talent-ops-team@evenuplaw.com. Examples of fraudulent email domains include “careers-evenuplaw.com” and “careers-evenuplaws.com”. Benefits & Perks:Our goal is to empower every team member to contribute to our mission of fostering a more just world, regardless of their role, location, or level of experience. To that end, here is a preview of what we offer:Choice of medical, dental, and vision insurance plans for you and your familyFlexible paid time off10 US observed holidays, and Canadian statutory holidays by provinceA home office stipend401(k) for US-based employeesPaid parental leaveSabbatical programA meet-up program to get together in person with colleagues in your areaOffices in San Francisco and TorontoPlease note the above benefits & perks are for full-time employees About EvenUp:EvenUp is on a mission to level the playing field in personal injury cases. EvenUp applies machine learning and its AI model known as Piai™ to reduce manual effort and maximize case outcomes across the personal injury value chain. Combining in-house human legal expertise with proprietary AI and software to analyze records. The Claims Intelligence Platform™ provides rich business insights, AI workflow automation, and best-in-class document creation for injury law firms. EvenUp is the trusted partner of personal injury law firms. Backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures (BCV), SignalFire, NFX, DCM, and more, EvenUp’s customers range from top trial attorneys to America’s largest personal injury firms. EvenUp was founded in late 2019 and is headquartered in San Francisco. Learn more at www.evenuplaw.com.EvenUp is an equal opportunity employer. We are committed to diversity and inclusion in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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Why HarveyHarvey is a secure AI platform for legal and professional services that augments productivity and automates complex workflows. Harvey uses algorithms with reasoning-adept LLMs that have been customized and developed by our expert team of lawyers, engineers and research scientists. We’ve found product market fit and are scaling our team very quickly. Some reasons to join Harvey are:Exceptional product market fit: We have partnered with the largest law firms and professional service providers in the world, including Paul Weiss, A&O Shearman, Ashurst, O'Melveny & Myers, PwC, KKR, and many others.Strategic investors: Raised over $500 million from strategic investors including Sequoia, Google Ventures, Kleiner Perkins, and OpenAI.World-class team: Harvey is hiring the best talent from DeepMind, Google Brain, Stripe, FAIR, Tesla Autopilot, Glean, Superhuman, Figma, and more.Partnerships: Our engineers and researchers work directly with OpenAI to build the future of generative AI and redefine professional services.Performance: 4x ARR in 2024.Competitive compensation.Role OverviewWe’re looking for a versatile Senior Analytics Engineer to architect the data backbone that powers decision-making at Harvey. With product-market fit already proven and demand surging across diverse customer segments, you’ll design clean, reliable pipelines and semantic data models that turn raw events into immediately usable insights. As the first Analytics Engineer on our team, you’ll choose and implement the right data stack, champion best practices in testing and documentation, and collaborate closely with product, GTM, and leadership to ensure every team can answer its own questions with confidence. If you combine engineering rigor with a love of storytelling through data—and want to shape analytics from the ground up—we’d love to meet you.What You’ll DoDesign and build scalable data models and pipelines using dbt to transform raw data into clean, reliable assets that power company-wide analytics and decision-making.Define and implement a robust semantic layer (e.g. LookML/Omni) that standardizes key business metrics, dimensions, and data products, ensuring self-serve capabilities for stakeholders across teams.Partner cross-functionally with Product, GTM, Finance, and the Exec Team to deliver intuitive, consistent dashboards and analytical tools that surface real-time business health metrics.Establish and champion data modeling standards and best practices, guiding the organization in how to model data for accuracy, usability, and long-term maintainability.Collaborate with engineering to make key decisions on data architecture, co-design data schemas, and implement orchestration strategies that ensure reliability and performance of the data warehouse.Lead data governance initiatives, ensuring high standards of data quality, consistency, documentation, and access control across the analytics ecosystem.Empower stakeholders with data by making analytical assets easily discoverable, reliable, and well-documented—turning complex datasets into actionable insights for the business. What You Have5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or similar fieldDeep expertise in SQL, dbt, Python, and modern BI/semantic layer tools like Looker or Omni.Skilled at defining core business and product metrics, uncovering insights, and resolving data inconsistencies across complex systems.Strong familiarity with version control (GitHub), CI/CD, and modern development workflows.Bias for action — you prefer launching usable, iterative data models that deliver immediate value over waiting for perfect solutions.Strong communicator who can build trusted partnerships across Product, GTM, Finance, and Exec stakeholders.Comfortable working through ambiguity in fast-moving, cross-functional environments.Balances big-picture thinking with precision in execution — knowing when to sweat the details and when to move quickly.Experience operating in a B2B or commercial setting, with an understanding of customer lifecycle and revenue-driving metrics.BonusEarly employee at a hyper-growth startupExperience with or knowledge of AI and LLMsData Engineering ExperienceExperience managing data warehouse (preferably Snowflake)Experience at world-class enterprise orgs (ex: Brex, Ramp, Stripe, Palantir)Compensation Range $170,000 - $200,000 USDPlease find our CA applicant privacy notice here.Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing interview-help@harvey.ai.

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About HeyGen At HeyGen, our mission is to make visual storytelling accessible to all. Over the last decade, visual content has become the preferred method of information creation, consumption, and retention. But the ability to create such content, in particular videos, continues to be costly and challenging to scale. Our ambition is to build technology that equips more people with the power to reach, captivate, and inspire audiences. Learn more at www.heygen.com.  Visit our Mission and Culture doc here. Position Summary: At HeyGen, we are at the forefront of developing applications powered by our cutting-edge AI research. As a Data Infrastructure Engineer, you will lead the development of fundamental data systems and infrastructure. These systems are essential for powering our innovative applications, including Avatar IV, Photo Avatar, Instant Avatar, Interactive Avatar, and Video Translation. Your role will be crucial in enhancing the efficiency and scalability of these systems, which are vital to HeyGen's success.   Key Responsibilities: Design, build, and maintain the data infrastructure and systems needed to support our AI applications. Examples include Large scale data acquisition Multi-modal data processing framework and applications Storage and computation efficiency AI model evaluation and productionization infrastructure Collaborate with data scientists and machine learning engineers to understand their computational and data needs and provide efficient solutions. Stay up-to-date with the latest industry trends in data infrastructure technologies and advocate for best practices and continuous improvement. Assist in budget planning and management of cloud resources and other infrastructure expenses. Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field Proven experience in managing infrastructure for large-scale AI or machine learning projects Excellent problem-solving skills and the ability to work independently or as part of a team. Proficiency in Python Experience optimizing computational workflows Familiarity with AI and machine learning frameworks like TensorFlow or PyTorch. Preferred Qualifications: Experience with GPU computing Experience with distributed data processing system Experience building large scale batch inference system Prior experience in a startup or fast-paced tech environment. What HeyGen Offers Competitive salary and benefits package. Dynamic and inclusive work environment. Opportunities for professional growth and advancement. Collaborative culture that values innovation and creativity. Access to the latest technologies and tools.   HeyGen is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.So, what’s the role all about? Within Actimize, the AI and Analytics Team is developing the next generation advanced analytical cloud platform that will harness the power of data to provide maximum accuracy for our clients’ Financial Crime programs. As part of the PaaS/SaaS development group, you will be responsible for developing this platform for Actimize cloud-based solutions and to work with cutting edge cloud technologies.  How will you make an impact? NICE Actimize is the largest and broadest provider of financial crime, risk and compliance solutions for regional and global financial institutions & has been consistently ranked as number one in the space At NICE Actimize, we recognize that every employee’s contributions are integral to our company’s growth and success. To find and acquire the best and brightest talent around the globe, we offer a challenging work environment, competitive compensation, and benefits, and rewarding career opportunities. Come share, grow and learn with us – you’ll be challenged, you’ll have fun and you’ll be part of a fast growing, highly respected organization. This new SaaS platform will enable our customers (some of the biggest financial institutes around the world) to create solutions on the platform to fight financial crime. Have you got what it takes? Design, implement, and maintain real-time and batch data pipelines for fraud detection systems. Automate data ingestion from transactional systems, third-party fraud intelligence feeds, and behavioral analytics platforms. Ensure high data quality, lineage, and traceability to support audit and compliance requirements. Collaborate with fraud analysts and data scientists to deploy and monitor machine learning models in production. Monitor pipeline performance and implement alerting for anomalies or failures. Ensure data security and compliance with financial regulations Qualifications: Bachelor’s or master’s degree in computer science, Data Engineering, or a related field. 4-6 years of experience in DataOps role, preferably in fraud or risk domains. Strong programming skills in Python and SQL. Knowledge of financial fraud patterns, transaction monitoring, and behavioral analytics. Familiarity with fraud detection systems, rules engines, or anomaly detection frameworks. Experience with AWS cloud platforms Understanding of data governance, encryption, and secure data handling practices. Experience with fraud analytics tools or platforms like Actimize What’s in it for you? Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr! Enjoy NiCE-FLEX! At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. Requisition ID: 7822 Reporting into: Director Role Type: Tech ManagerAbout NiCE NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions. Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries. NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.  

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Lambda is the #1 GPU Cloud for ML/AI teams training, fine-tuning and inferencing AI models, where engineers can easily, securely and affordably build, test and deploy AI products at scale. Lambda’s product portfolio includes on-prem GPU systems, hosted GPUs across public & private clouds and managed inference services – servicing government, researchers, startups and Enterprises world-wide. If you'd like to build the world's best deep learning cloud, join us.  *Note: This position requires presence in our San Francisco office location 4 days per week; Lambda’s designated work-from-home day is currently Tuesday. Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance. Most people are aware that the AI revolution is driven by data. What most people don’t know is that this data is hosted on large, high-performance storage arrays measured in petabytes. At Lambda, the Infrastructure Storage Team’s job is to ensure that the data powering AI is fast, performant, and available.The Storage team is a multidisciplinary group of Storage Engineers, Software Engineers, and SREs. This close-knit team is motivated by a shared passion for delivering top-tier storage solutions to our customers. As both a product and operations team, we collaborate closely to accelerate development, deployment, and, most importantly, build resilient storage offerings.We are looking for a Ceph subject matter expert to support our latest Storage initiative. Starting with Object Storage, Ceph will form the backbone of our next-generation, differentiated storage solutions. The ideal candidate will train current Storage Engineers, advise on key Ceph decisions, and drive strategic Ceph initiatives.What You’ll Do:Design, deploy, and maintain highly available 40PB+ Ceph clustersPerform cluster upgrades, expansions, and performance optimizationsConfigure and optimize RBD, CephFS, and RadosGW servicesMonitor cluster health, performance metrics, and capacity utilizationDevelop capacity planning models and growth projectionsTrain others on CephYou Have:Bachelor's degree in Computer Science, Engineering, or equivalent experience5+ years of experience in storage engineering or distributed systems5+ years of hands-on experience with Ceph administration and troubleshootingStrong understanding of storage protocols (NFS, iSCSI, S3, Swift)Proficiency with Linux system administration and storage subsystemsExperience with storage hardware (SSDs, HDDs, NVMe) and networking technologiesKnowledge of monitoring tools (Prometheus, Grafana, Nagios) and log analysisUnderstanding of data protection concepts, backup strategies, and disaster recoveryNice to HaveCeph Certified Professional or equivalent certificationExperience with other distributed storage systems (GlusterFS, HDFS, MinIO)Experience with public cloud storage services (AWS S3, Azure Blob, GCP)Familiarity with storage benchmarking tools (fio, rados bench, COSBench)Experience with programming in Go is strongly preferred.Experience with configuration management tools (Ansible, Puppet, Chef)Understanding of network protocols and storage networking (RDMA, iSER)Salary Range InformationBased on market data and other factors, the annual salary range for this position is $380,000-$460,000. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. About LambdaFounded in 2012, ~350 employees (2024) and growing fastWe offer generous cash & equity compensationOur investors include Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, US Innovative Technology, Gradient Ventures, Mercato Partners, SVB, 1517, Crescent Cove.We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitabilityOur research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOGHealth, dental, and vision coverage for you and your dependentsWellness and Commuter stipends for select roles401k Plan with 2% company match (USA employees)Flexible Paid Time Off Plan that we all actually useA Final Note:You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.Equal Opportunity EmployerLambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

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Worth AI, a leader in the computer software industry, is looking for a talented and experienced Senior Data Engineer to join their innovative team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence while fostering an environment of collaboration, and adaptability, aiming to make a meaningful impact in the tech landscape.. Our team values include extreme ownership, one team and creating reaving fans both for our employees and customers.As a Senior Data Engineer, you will lead the design and development of data services and platforms that power our AI-driven products. You'll focus on creating well-structured, validated APIs and event-driven pipelines, enabling scalable, secure, and maintainable data workflows. This is a backend-heavy role ideal for engineers who thrive on clean architecture, automation, and cross-functional delivery.Responsibilities Design and build production-grade **FastAPI services** to serve, validate, and enrich data for ML and analytics use cases Create and maintain **asynchronous event-driven pipelines** using  *Apache Kafka**, ensuring reliable and scalable communication across microservices Define and enforce structured data contracts using **Pydantic** and OpenAPI standards Develop robust, containerized data services with **Docker** and deploy them using modern cloud-native tooling Build and optimize analytical models and data flows in **Amazon Redshift** for business-critical reporting and data science consumption Collaborate with data scientists, ML engineers, and backend developers to streamline data sourcing, transformation, and model inference Own the lifecycle of data services — including monitoring, observability, testing, and deployment pipelines Maintain rigorous standards around data privacy, schema governance, and system performance Design, build, code and maintain large-scale data processing systems and architectures that support AI initiatives. Develop and implement data pipelines and ETL processes to ingest, transform, and load data from various sources. Design and optimize databases and data storage solutions for high performance and scalability. Collaborate with cross-functional teams to understand data requirements and ensure data quality and integrity. Implement data governance and data security measures to protect sensitive data. Monitor and troubleshoot data infrastructure and pipeline issues in a timely manner. Stay up-to-date with the latest trends and technologies in data engineering and recommend improvements to enhance the company's data capabilities. Requirements 7+ years of professional experience in backend-focused data engineering or platform development Strong proficiency in **Python**, with hands-on experience using **FastAPI**, **Pydantic**, and asynchronous programming patterns Deep understanding of **event-driven architectures** and experience with **Kafka** (producers, consumers, schema evolution, retries, etc.) Experience designing and deploying **containerized services** with **Docker** (Kubernetes or Fargate experience is a plus) Proficiency in SQL and experience with modern cloud data warehouses, preferably **Amazon Redshift** Familiarity with cloud services (preferably AWS), including CI/CD, infrastructure-as-code, and observability tooling Experience integrating third-party APIs and working with versioned schema contracts Strong communication and collaboration skills, especially in cross-functional and agile teams Experience working with ML engineers to operationalize models (e.g., batch scoring, online inference, data validation at model boundaries) In-depth knowledge of data modeling, data warehousing, and database design principles. Strong programming skills in Python, SQL, and other relevant languages. Experience with relational and NoSQL databases, such as PostgreSQL, MySQL, MongoDB Proficiency in data integration and ETL tools, such as Apache Kafka, Apache Airflow, or Informatica. Familiarity with big data processing frameworks, such as Hadoop, Spark, or Flink. Knowledge of cloud platforms, such as AWS, Azure, or GCP, and experience with data storage and processing services in the cloud. Understanding of data governance, data privacy, and data security best practices. Strong problem-solving and troubleshooting skills, with a focus on data quality and system performance. Excellent communication and collaboration skills to work effectively with cross-functional teams. Prior collaborative work with data scientists or machine learning professionals with respect to sourcing, processing and scaling both input and output data Comfortable going through documentation of third-party API’s and identifying best procedures for integrating data from API’s into broader ETL processes  Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance Unlimited Paid Time Off 9 paid Holidays Family Leave Work From Home Free Food & Snacks (Access to Industrious Co-working Membership!) Wellness Resources

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Worth AI, a leader in the computer software industry, is looking for a talented and experienced Data Infrastructure Engineer to join their innovative team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence while fostering an environment of collaboration, and adaptability, aiming to make a meaningful impact in the tech landscape.. Our team values include extreme ownership, one team and creating reaving fans both for our employees and customers.Worth is looking for a Data Infrastructure Engineer to build and maintain the foundational systems that power our data platform. In this role, you will design, implement, and optimize scalable, reliable, and secure data infrastructure that supports analytics, data science, and product applications across the company.The ideal candidate is deeply experienced with modern data architectures, cloud platforms, and data orchestration tools. You are passionate about automation, performance tuning, and ensuring high availability of data services. This is a critical role on our data team and offers the opportunity to shape the long-term data strategy of the organization.Responsibilities Design, build, and maintain scalable and resilient data infrastructure in a cloud environment (AWS, Azure, or GCP). Develop and maintain ETL/ELT pipelines using orchestration tools such as Airflow, Dagster, or dbt. Optimize data workflows for reliability, performance, and cost efficiency across structured and unstructured datasets. Manage data lake and data warehouse environments (e.g., Snowflake, BigQuery, Redshift, Delta Lake). Ensure data security, privacy, and compliance, including role-based access control, data encryption, and audit logging. Collaborate with data scientists, analysts, and product teams to ensure data accessibility, accuracy, and availability. Support real-time and batch data processing frameworks, including Kafka, Spark, Flink, or similar tools. Monitor, troubleshoot, and improve the observability and performance of data systems using tools like Prometheus, Grafana, or Datadog. Maintain CI/CD pipelines for data infrastructure using Terraform, GitHub Actions, or similar tools. Requirements 5+ years of experience in data engineering, infrastructure engineering, or a related field. Strong programming skills in Python, Node.js. Proficient in SQL and experience with distributed query engines (e.g., Trino, Presto). Experience with cloud-native data platforms such as AWS Glue Hands-on experience with infrastructure-as-code tools (Terraform, Pulumi, CloudFormation). Familiarity with containerization and orchestration tools such as Kafka and Kubernetes. Solid understanding of data governance, quality frameworks, and data lifecycle management. Ability to work in a fast-paced, collaborative environment with a focus on impact and delivery. Experience in streaming data architecture and tools like Apache Kafka, Kinesis, or Pub/Sub. Background in supporting machine learning or analytics platforms. Exposure to data mesh, data contracts, or modern data stack concepts. Knowledge of DevOps principles applied to data systems. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance Unlimited Paid Time Off 9 paid Holidays Family Leave Work From Home Free Food & Snacks (Access to Industrious Co-working Membership!) Wellness Resources

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Worth AI, a leader in the computer software industry, is looking for a talented and experienced VP of Data, Analytics and AI to join their innovative team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence while fostering an environment of collaboration, and adaptability, aiming to make a meaningful impact in the tech landscape.. Our team values include extreme ownership, one team and creating reaving fans both for our employees and customers.Worth AI is seeking a strategic and hands on and execution-oriented Vice President of Data to lead our data function as we scale. This role is central to shaping how data is acquired, structured, commercialized, and governed across the company. The ideal candidate brings deep experience in data strategy, monetization opportunities, and operational excellence—transforming data into a key business asset that drives commercial value, innovation, and competitive advantage. Our Vice President of Data will have distinct expertise in credit modeling and experience collaborating with third-party data providers. This role requires a dynamic leader to drive our data strategy, combining innovative risk solutions with top-tier data science, machine learning, and AI methodologies.ResponsibilitiesHands-On Leadership & Team Management Lead a growing team of approximately five data professionals across engineering, analytics, data science, and governance. Be a hands-on leader who actively engages in code reviews, model reviews, and technical deep dives to stay connected to the day-to-day realities of engineering and data science work. Set a high technical bar while mentoring and developing team members, fostering a culture of innovation, ownership, and collaboration. Data Acquisition & Partnerships Lead the end-to-end strategy for acquiring first-party, second-party, and third-party data sources aligned to business priorities. Evaluate and negotiate data licensing agreements and strategic partnerships to grow our data asset portfolio. Design robust, scalable, and compliant ingestion pipelines for efficient data integration and enrichment. Risk, Fraud, and Credit Model Development Utilize data science, machine learning, and AI techniques to design, test, and deploy advanced risk, fraud, and credit scoring models.Commercial Applications of Data Identify, define, and execute on opportunities to monetize data assets—both directly and through data-enabled products and services. Partner closely with Product, Sales, Marketing, Strategy, and Customer Success to integrate data insights into go-to-market initiatives and client-facing solutions. Translate data into actionable business intelligence that informs strategy and drives measurable business growth. Scalability & Operational Excellence Build scalable, repeatable processes for data management—spanning integration, transformation, quality assurance, and delivery. Champion the adoption of modern data platforms and tools (e.g., Snowflake, Databricks, dbt) to support real-time decision-making and automation. Develop and lead a high-performing data team across engineering, analytics, data science, and governance, fostering a culture of innovation, collaboration, and accountability. Data Governance & Compliance Own and evolve data governance frameworks to ensure integrity, quality, security, and compliance with global regulations (e.g., GDPR, CCPA). Establish clear data ownership and stewardship models, along with standardized policies for access, lineage, and privacy. Proactively manage data risk and embed ethical practices into all aspects of data use and monetization. Cross-Functional Collaboration Partner with engineering, product, finance, and other internal teams to ensure alignment on data initiatives. Serve as the internal advocate for data as a strategic asset, ensuring organizational alignment around data value and strategy. Requirements Bachelor’s or Master’s  in Data Science, Computer Science, Statistics, or a related discipline 10+ years in data leadership roles, including at least 5 years leading large-scale data initiatives in fast-paced, data-driven environments. Experience with risk technology or credit modeling in enterprise contexts is a strong plus. Proven expertise in monetizing data assets and building governance structures at scale. Strong understanding of data platforms (e.g., Snowflake, Databricks), cloud architecture, data pipelines, and modern analytics tooling. Demonstrated ability to lead multidisciplinary teams, craft vision and strategy, and drive tactical execution. Outstanding communication and stakeholder management skills, with the ability to convey complex data concepts to technical and non-technical audiences. Deep experience in data science, machine learning, AI, and credit or risk modeling. Strong problem-solving and data interpretation skills with a focus on delivering results. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance Unlimited Paid Time Off 9 paid Holidays Family Leave Work From Home Free Food & Snacks (Access to Industrious Co-working Membership!) Wellness Resources

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About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.About the role As an early member of our Finance Analytics and Business Intelligence team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by establishing robust analytics engineering and business intelligence capabilities for our Accounting organization. In this unique company, technology, and moment in history, your work will be critical to ensuring accurate financial reporting, streamlining accounting processes, and supporting our financial operations as we deploy safe, frontier AI at scale to the world.  As the first Finance Analytics and BI member focused on Accounting and Corporate Finance & Strategy, you will use advanced analytics to drive strategic decision-making and sound operations for our accounting teams. You'll work at the intersection of finance, analytics, and business intelligence to develop automated reporting systems, data quality frameworks, and scaled insights that support our various business models and entities. You’ll partner closely with Data Infrastructure, Finance Systems, and the Accounting organization: Corporate Accounting, Revenue Accounting, Technical Accounting, International Accounting, and Finance Operations (FinOps). You've worked in cultures of excellence in the past and are eager to apply that experience to building robust and scalable systems and processes as our company goes through a phase of rapid growth. Responsibilities: Establish the foundation for accounting analytics and BI at Anthropic, creating processes and best practices for financial data management, governance, and reporting Build and maintain automated financial reporting systems, dashboards, and solutions that provide real-time insights to accounting and finance leadership Develop sophisticated revenue recognition analytics and monitoring to support our subscription- and consumption-based business model Partner with Accounting teams (Corporate, International, Technical, Revenue, FinOps) to streamline close processes and financial reporting Design and implement audit support systems and documentation processes to facilitate external audits and compliance requirements Partner with Data Infrastructure, Analytics Engineering, and Financial Systems teams to develop scalable data pipelines and infrastructure supporting accounting analytics Champion data-informed decision making across the organization You may be a good fit if you: Have 6+ years of experience in finance analytics, business intelligence, or financial systems analysis with demonstrated experience partnering with Accounting, Data Infrastructure, and Financial Systems teams Are highly proficient in SQL and Python for data manipulation, analysis, and automation Have extensive experience with BI visualization tools such as Looker, Tableau; and have experience with cloud platforms (AWS, GCP) and modern data stack tools (dbt, Airflow, etc.) Have hands-on experience working with financial systems like NetSuite, Stripe, or other ERP/financial platforms, and building downstream data models from these systems Possess strong financial acumen with deep understanding of accounting principles (GAAP vs. non-GAAP, revenue recognition), financial statements, and corporate finance processes Have a proven track record of collaborating with finance stakeholders to deliver impactful analytical solutions and process improvements Excel at translating complex business requirements into technical solutions and can communicate effectively with both technical and non-technical stakeholders Are detail-oriented with a commitment to data accuracy and have experience building robust, scalable analytical solutions Thrive in fast-paced environments and can manage multiple priorities while maintaining high-quality deliverables Have experience with data modeling, ETL processes, and building automated reporting solutions Strong candidates may have: Relevant certifications in financial systems or business intelligence platforms Prior experience in high-growth technology companies or startups Knowledge of statistical analysis and advanced analytics techniques Experience with financial planning and analysis (FP&A) processes and systems Familiarity with data governance best practices and experience implementing data quality frameworks The expected salary range for this position is:Annual Salary:$265,000—$315,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.