Top Machine Learning Engineer Jobs Openings in 2025

Looking for opportunities in Machine Learning Engineer? This curated list features the latest Machine Learning Engineer job openings from AI-native companies. Whether you're an experienced professional or just entering the field, find roles that match your expertise, from startups to global tech leaders. Updated everyday.

NiCE.jpg

Data Scientist Engineer

Nice
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IN.svg
India
Remote
false
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? The Prompt Engineer optimizes prompts to generative AI models across NiCE's Illuminate applications. As part of the Illuminate Research team, the Prompt Engineer works with several groups in the business to help our applications deliver the highest quality customer experience. The Prompt Engineer partners with global development teams to help diagnose and resolve prompt-based issues. This includes helping to define and execute tests for LLM-based systems that are difficult to evaluate with traditional test automation tools. The Prompt Engineer also helps educate the development teams on advances in prompt engineering and helps update production prompts to evolving industry best practices.   How will you make an impact? Regularly review production metrics and specific problem cases to find opportunities for improvement. Help diagnose and resolve issues with production prompts in English. Refine prompts to generative AI systems to achieve customer goals. Collect and present quantitative analysis on solution success. Work with application developers to implement new production monitoring tools and metrics. Work with architects and Product Managers to implement prompts to support new features. Meet regularly with teams working in United States Mountain and Pacific time zones (UTC-7:00 and UTC-8:00). Review new prompts and prompt changes with Machine Learning Engineers. Consult with Machine Learning Engineers for more challenging problems. Stay informed about new advances in prompt engineering.   Have you got what it takes?   Fluent in written and spoken English. BS in technology-related field such as computer science, business intelligence/analytics, or finance. 2-4 years' work experience in a technology-related industry or position. Familiarity with best practices in prompt engineering, to include differences in prompts between major LLM vendors. Ability to develop and maintain good working relationships with cross-functional teams. Ability to clearly communicate and present to internal and external stakeholders. Experience with Python and at least one web app framework for prototyping, e.g., Streamlit or Flask.   You will have an advantage if you also have Basic AWS resource management, including microservice deployment. Containerization via Docker. Experience with both standard and AI-based testing frameworks such as PyTest and DeepEval. Exposure to generative AI application frameworks like LangChain, LlamaIndex, and griptape   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: 8429 Reporting into: Tech Manager Role Type: Individual ContributorAbout 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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Machine Learning Engineer - Defence

Faculty
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GB.svg
United Kingdom
Full-time
Remote
false
About Faculty At Faculty, we transform organisational performance through safe, impactful and human-centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.Because of the potential to work with our UK Defence clients, you will need to be eligible for UK SC clearance and willing to work up to three days per week on site with these customers, which may require travel to locations outside of our London base. The minimum requirement for SC clearance is 5 years continuous residence in the UK up to the present.About the RoleYou will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. The work you do will help our customers solve a broad range of high-impact problems in the Defence and National Security arena. What You'll Be DoingYou are engineering-focused, with a keen interest and working knowledge of operationalised machine learning. You have a desire to take cutting-edge ML applications into the real world. You will develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements. You will support both technical, and non-technical stakeholders, to deploy ML to solve real-world problems. Our Machine Learning Engineers are responsible for the engineering aspects of our customer delivery projects. As a Machine Learning Engineer, you’ll be essential to helping us achieve that goal by:Building software and infrastructure that leverages Machine Learning;Creating reusable, scalable tools to enable better delivery of ML systemsWorking with our customers to help understand their needsWorking with data scientists and engineers to develop best practices and new technologies; andImplementing and developing Faculty’s view on what it means to operationalise ML software.As a rapidly growing organisation, roles are dynamic and subject to change. Your role will evolve alongside business needs, but you can expect your key responsibilities to include:Working in cross-functional teams of engineers, data scientists, designers and managers to deliver technically sophisticated, high-impact systems.Working with senior engineers to scope projects and design systemsProviding technical expertise to our customersTechnical DeliveryWho We're Looking ForYou can view our company principles here. We look for individuals who share these principles and our excitement to help our customers reap the rewards of AI responsibly.To succeed in this role, you’ll need the following - these are illustrative requirements and we don’t expect all applicants to have experience in everything (70% is a rough guide):Understanding of, and experience with the full machine learning lifecycleWorking with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorchExperience with software engineering best practices and developing applications in Python.Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud providers (AWS, GCP or Azure)Demonstrable experience with containers and specifically Docker and KubernetesAn understanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniquesDemonstrable experience of managing/mentoring more junior members of the team Outstanding verbal and written communication.Excitement about working in a dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to executionWe like people who combine expertise and ambition with optimism -- who are interested in changing the world for the better -- and have the drive and intelligence to make it happen. If you’re the right candidate for us, you probably:Think scientifically, even if you’re not a scientist - you test assumptions, seek evidence and are always looking for opportunities to improve the way we do things.Love finding new ways to solve old problems - when it comes to your work and professional development, you don’t believe in ‘good enough’. You always seek new ways to solve old challenges.Are pragmatic and outcome-focused - you know how to balance the big picture with the little details and know a great idea is useless if it can’t be executed in the real world.What we can offer you: The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.
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Machine Learning, Platform Engineer

Together AI
USD
0
160000
-
250000
US.svg
United States
Full-time
Remote
false
This role focuses on enabling custom models and dedicated inference on Together. We are responsible for optimizing autoscaling, minimizing cold starts, achieving the best end-to-end model performance, and providing a best-in-class developer experience with great tooling. Required Qualifications 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems and API microservices Experience running serverless inference platforms, doing model bring-up on short notice, being on call, or general cloud provider is a very big plus Good taste and ability to thoughtfully discuss how what you’ve built has failed over time Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources Excellent understanding of low level operating systems concepts including concurrency, networking and storage, performance and scale Expert-level programmer in one or more of Golang, Rust, Python, C++, or Haskell Proficiency in writing and maintaining Infrastructure as Code (IaC) using tools like Terraform Experience with Kubernetes or other container orchestration systems Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience Writing-heavy roles or companies are a plus Key Responsibilities New hires may work on multi-cluster orchestration, portfolio optimization, predictive autoscaling, control panes, model bring-up, light model optimization, APIs for managing deployments, inference worker SDKs, and CLI tools. Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure Partner with product teams to understand functional requirements and deliver solutions that meet business needs Write clear, well-tested, and maintainable software and IaC for both new and existing systems Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $250,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy  
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AI Engineer - FDE (Forward Deployed Engineer)

Databricks
USD
161280
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225792
US.svg
United States
Full-time
Remote
true
CSQ426R189 The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote. The impact you will have: Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems Own production rollouts of consumer and internally facing GenAI applications Serve as a trusted technical advisor to customers across a variety of domains Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy Expertise in deploying production-grade GenAI applications, including evaluation and optimizations  Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience building production-grade machine learning deployments on AWS, Azure, or GCP Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike Passion for collaboration, life-long learning, and driving business value through AI [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets   Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.  Zone 1 Pay Range$161,280—$225,792 USDZone 2 Pay Range$161,280—$225,792 USDZone 3 Pay Range$161,280—$225,792 USDZone 4 Pay Range$161,280—$225,792 USDAbout Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks.  Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
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Member of Engineering (Pre-training and inference software)

Poolside
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No items found.
Full-time
Remote
true
ABOUT POOLSIDEIn this decade, the world will create artificial intelligence that reaches human level intelligence (and beyond) by combining learning and search. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will determine who survives and wins. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research and engineering at scale. They will create powerful economic engines. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this.poolside exists to be one of these companies - to build a world where AI will drive the majority of economically valuable work and scientific progress.We believe that software development will be the first major capability in neural networks that reaches human-level intelligence because it's the domain where we can combine Search and Learning approaches the best.At poolside we believe our applied research needs to culminate in products that are put in the hands of people. Today we focus on building for a developer-led increasingly AI-assisted world. We believe that current capabilities of AI lead to incredible tooling that can assist developers in their day to day work. We also believe that as we increase the capabilities of our models, we increasingly empower anyone in the world to be able to build software. We envision a future where not 100 million people can build software but 2 billion people can.View GDPR PolicyABOUT OUR TEAMWe are a remote-first team that sits across Europe and North America and comes together once a month in-person for 3 days and for longer offsites twice a year.Our R&D and production teams are a combination of more research and more engineering-oriented profiles, however, everyone deeply cares about the quality of the systems we build and has a strong underlying knowledge of software development. We believe that good engineering leads to faster development iterations, which allows us to compound our efforts.ABOUT THE ROLEYou would be working in our pre-training team focused on building out our distributed training and inference of Large Language Models (LLMs). This is a hands-on role that focuses on software development best practices, maintenance, and code architecture. You will have access to thousands of GPUs to verify changes.Strong engineering skills are a prerequisite. We assume perfect knowledge of CI/CD, reliability concepts, software architecture, and code quality properties. A basic understanding of LLM training and inference principles is required. We look for fast learners who are prepared for a steep learning curve and are not afraid to step out of their comfort zone.YOUR MISSIONTo help train the best foundational models for source code generation in the worldRESPONSIBILITIESPropose and evaluate innovations in the training development experience and reliabilityEnhance and maintain our training and inference codebasesWrite high-quality Python (PyTorch), Cython, C/C++ code. Perform refactoringsImprove CI/CDSKILLS & EXPERIENCEUnderstanding of Large Language Models (LLM)Basic knowledge of TransformersKnowledge of deep learning fundamentalsStrong engineering backgroundProgramming experienceLinuxStrong algorithmic skillsPython with numpy, PyTorch, or JaxC/C++CI/CD, project maintenanceUse modern tools and are always looking to improveStrong critical thinking and ability to question code quality policies when applicablePROCESSIntro call with one of our Founding EngineersTechnical Interview(s) with one of our Founding EngineersTeam fit call with the People teamFinal interview with Eiso, our CTO & Co-FounderBENEFITSFully remote work & flexible hours37 days/year of vacation & holidaysHealth insurance allowance for you and dependentsCompany-provided equipmentWellbeing, always-be-learning and home office allowancesFrequent team get togethersGreat diverse & inclusive people-first culture
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Member of Technical Staff, Integration/RL Team (Research Engineer)

Cohere
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FR.svg
France
GB.svg
United Kingdom
CA.svg
Canada
Full-time
Remote
true
Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!The integration team is responsible for developing and scaling machine learning algorithms and infrastructure for LLM post-training, with a focus on large-scale, distributed RL methods. We strive for excellence in both engineering and science by meticulously designing experiments and design docs. While tasks are assigned according to everyone’s expertise, there is a global team effort to write production code and support the team research efforts, depending on individual interests and organizational needs.In particular, this role aims to enhance the global quality of the post-training codebase by implementing new tools to ease and support research, optimizing post-training algorithms, and scaling distributed RL to unprecedented levels.Please Note: We have offices in London, Paris, Toronto, San Francisco, New York but we are also remote-friendly! Applicants for this role may work anywhere between UTC−06:00 and UTC+01:00.As a Member of Technical Staff, you will:Design and write high-performing and scalable software for training models.Develop new tools to support and accelerate research and LLM training.Coordinate with other engineering teams (Infrastructure, Efficiency, Serving) and the scientific teams (Agent, Multimodal, Multilingual, etc.) to create a strong and integrated post-training ecosystem.Craft and implement techniques to improve performance and speed up our training cycles, both on SFT, offline preference, and the RL regime.Research, implement, and experiment with ideas on our cluster and data infrastructure.Collaborate, Collaborate, and Collaborate with other scientists, engineers, and teams!You are an ideal candidate if you have:Extremely strong software engineering skills.Value test-driven development methods, clean code, and strive to reduce technical debts at all levels.Proficiency in Python and related ML frameworks such as JAX, Pytorch and/or XLA/MLIR.Experience using and debugging large-scale distributed training strategies (memory/speed profiling).[Bonus] Experience with distributed training infrastructures (Kubernetes) and associated frameworks (Ray).[Bonus] Hands-on experience with the post-training phase of model training, with a strong emphasis on scalability and performance.[Bonus] Experience in ML, LLM and RL academic research.This role is perfect for you if you:Have a deep passion for quality work.Enjoy tuning and optimising large LLM models.Comfortable working with people with different levels of software engineering skills, from beginner to more advanced.Comfortable diving into complex ML codebases to identify and resolve issues, ensuring the smooth operation of our systems.Thrive in a fast-paced, technically challenging environment, where you can contribute your innovative ideas and solutions.If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! If you want to work really hard on a glorious mission with teammates that want the same thing, Cohere is the place for you.We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for 6 months for employees based in Canada, the US, and the UK🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco and London and co-working stipend✈️ 6 weeks of vacationNote: This post is co-authored by both Cohere humans and Cohere technology.
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Evaluation Scenario Writer - AI Agent Testing Specialist

Mindrift
USD
0
0
-
55
US.svg
United States
Part-time
Remote
true
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 RoleWe’re looking for someone who can design realistic and structured evaluation scenarios for LLM-based agents. You’ll create test cases that simulate human-performed tasks and define gold-standard behavior to compare agent actions against. You’ll work to ensure each scenario is clearly defined, well-scored, and easy to execute and reuse. You’ll need a sharp analytical mindset, attention to detail, and an interest in how AI agents make decisions.Although every project is unique, you might typically: Designing structured test scenarios based on real-world tasks Defining the golden path and acceptable agent behavior Annotating task steps, expected outputs, and edge cases Working with devs to test your scenarios and improve clarity Reviewing agent outputs and adapting tests accordingly 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 have a Bachelor's or Master’s degree in Computer Science, Software Engineering, Data Science / Data Analytics, Artificial Intelligence / Machine Learning, Computational Linguistics / Natural Language Processing (NLP), Information Systems or other related fields.  You have 3+ years of experience. Your level of English is advanced (C1) 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? Get paid for your expertise, with rates that can go up to $55/hour depending on your skills, experience, and project needs. 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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Applied Research Engineer, Agents

Labelbox
USD
0
250000
-
300000
US.svg
United States
PL.svg
Poland
Full-time
Remote
false
Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI. Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics. Role Overview As an Applied Research Engineer at Labelbox, you’ll sit at the junction of advanced AI research and real product impact, with a focus on the data that makes modern agents work—browser interactions, SWE/code traces, GUI sessions, and multi-turn workflows. You’ll drive the data landscape required to advance capable, adaptable agents and help shape Labelbox’s strategy for collecting, synthesizing, and evaluating it. You will possess expertise in LLM agents and planning/execution loops, plus creativity in tackling problems across data design, interaction, and measurement. You’ll publish meaningful results, collaborate with customer researchers in frontier AI labs, and turn prototypes into reliable, scalable features. Your Impact Create frameworks and tools to construct, train, benchmark and evaluate autonomous agent capabilities. Design agent-focused data programs using supervised fine-tuning (SFT) and reinforcement learning (RL) methodologies. Develop data pipelines from diverse sources like code repositories, web browsers, and computer systems. Implement and adapt popular open-source agent libraries and benchmarks with proprietary datasets and models. Engage with research teams in frontier AI labs and the wider AI community to understand evolving agent data needs for frontier models and share best practices. Collaborate closely with frontier AI lab customers to understand requirements and guide model development. Publish research findings in academic journals, conferences, and blog posts. What You Bring Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or related field. At least 3 years of experience addressing sophisticated ML problems with successful delivery to customers. Experience building and training autonomous agents—tool use, structured outputs, multi-step planning—across browsers/GUI, codebases, and databases using SFT and RL. Constructed and evaluated agentic benchmarks (e.g. SWE-bench, WebArena, τ-bench, OSWorld) and reliability/efficiency suites (e.g. WABER).  Adept at interpreting research literature and quickly turning new ideas into prototypes. Deep understanding of frontier models (autoregressive, diffusion), post-training (SFT, RLVR, RLAIF, RLHF, et al.), and their human data requirements. Proficient in Python, data science libraries and deep learning frameworks (e.g., PyTorch, JAX, TensorFlow). Strong analytical and problem-solving abilities in ambiguous situations. Excellent communication skills. Track record of publications in top-tier AI/ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, etc.). Labelbox Applied Research At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios. We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new ideas, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of human-centric AI development, setting new standards for how AI systems learn from and interact with humans.Labelbox strives to ensure pay parity across the organization and discuss compensation transparently.  The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.Annual base salary range$250,000—$300,000 USDLife at Labelbox Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making Growth: Career advancement opportunities directly tied to your impact Vision: Be part of building the foundation for humanity's most transformative technology Our Vision We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs. Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs. Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice. Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.
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Senior Machine Learning Engineer

Faculty
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GB.svg
United Kingdom
Full-time
Remote
false
About Faculty At Faculty, we transform organisational performance through safe, impactful and human-centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.We operate a hybrid way of working, meaning that you'll split your time across client location, Faculty's Old Street office and working from home depending on the needs of the project. For this role, you can expect to be client-side for up-to three days per week at times and working either from home or our Old street office for the rest of your time. What You'll Be DoingWorking in our Defence business unit You will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. The work you do will help our customers solve a broad range of high-impact problems in the defence and national security space - examples of which can be found hereYou are engineering-focused, with a keen interest and working knowledge of operationalised machine learning. You have a desire to take cutting-edge ML applications into the real world. You will develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements. You will support both technical and non-technical stakeholders to deploy ML to solve real-world problems. To enable this, we work in cross-functional teams with representation from commercial, data science, product management and design specialities to cover all aspects of AI product delivery.The Machine Learning Engineering team is responsible for the engineering aspects of our customer delivery projects. As a Machine Learning Engineer, you’ll be essential to helping us achieve that goal by:Building software and infrastructure that leverages Machine Learning;Creating reusable, scalable tools to enable better delivery of ML systemsWorking with our customers to help understand their needsWorking with data scientists and engineers to develop best practices and new technologies; andImplementing and developing Faculty’s view on what it means to operationalise ML software.We’re a rapidly growing organisation, so roles are dynamic and subject to change. Your role will evolve alongside business needs, but you can expect your key responsibilities to include: Working in cross-functional teams of engineers, data scientists, designers and managers to deliver technically sophisticated, high-impact systems.Leading on the scope and design of projectsOffering leadership and management to more junior engineers on the team Providing technical expertise to our customersTechnical DeliveryWho We're Looking ForAt Faculty, your attitude and behaviour are just as important as your technical skill. We look for individuals who can support our values, foster our culture, and deliver for our organisation.We like people who combine expertise and ambition with optimism -- who are interested in changing the world for the better -- and have the drive and intelligence to make it happen. If you’re the right candidate for us, you probably:Think scientifically, even if you’re not a scientist - you test assumptions, seek evidence and are always looking for opportunities to improve the way we do things.Love finding new ways to solve old problems - when it comes to your work and professional development, you don’t believe in ‘good enough’. You always seek new ways to solve old challenges.Are pragmatic and outcome-focused - you know how to balance the big picture with the little details and know a great idea is useless if it can’t be executed in the real world.To succeed in this role, you’ll need the following - these are illustrative requirements and we don’t expect all applicants to have experience in everything (70% is a rough guide):Understanding of and interest in the full machine learning lifecycle, including deploying trained machine learning models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorchUnderstanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniquesExperience in Software Engineering including programming in Python.Technical experience of cloud architecture, security, deployment, and open-source tools. Hands-on experience required of at least one major cloud platformDemonstrable experience with containers and specifically Docker and KubernetesComfortable in a high-growth startup environment.Outstanding verbal and written communication.Excitement about working in a dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to executionWhat we can offer you: The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.
Machine Learning Engineer
Data Science & Analytics
DevOps Engineer
Data Science & Analytics
Software Engineer
Software Engineering
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Manager Forward Deployed Engineering

Taktile
USD
0
250000
-
315000
US.svg
United States
Full-time
Remote
false
About The RoleTaktile is a high-growth, post product-market-fit start-up, on a fast trajectory to becoming market leader in the field of automated decisioning. We are looking for a Forward Deployed Engineer Manager to help us transform how our customers make critical business decisions by overseeing a team of Forward Deployed Engineers onboarding them onto Taktile and ensuring they get real value from our platform. You ensure your team acts as a trusted advisor and supports customers in reaching their goals while maximizing Taktile’s impact.If you’re passionate about tech and AI, and have extensive experience with Python, SQL, and REST APIs, you’ll thrive here.What You'll do as Forward Deployed Engineering ManagerOversee Taktile deployments in production, technical delivery across multiple projects from scoping to stable production traffic.Apply technical expertise, problem-solving skills and creativity to help organizations address real-world challenges by partnering and problem solving with your team members. Your day could include reviewing solution architectures, co-developing decision logic or AI agents, or aligning with key customer stakeholders together with your team members.Reliably review solution design and scoping proposals, sequence delivery, and proactively remove blockers. You are making thoughtful trade-offs between scope, speed, and quality to ensure successful and timely project delivery.Manage capacity of your team and partners with RevOps/Customer operations to improve or introduce scalable processes to the Forward Deployed Engineering teams at Taktile.Partner with Taktile’s product management team to turn your understanding of customer needs into actionable product insights, directly influencing the evolution of Taktile’s product roadmap.You play a key role in scaling the Forward Deployed Engineering function by creating reusable resources, best practices, and tools that share your expertise and drive organizational growthYou actively coach and mentor Forward Deployed Engineers on your team, supporting their development and success.You hire, grow and retain a team of exceptional Forward Deployed Engineers.About YouYou bring 8+ years of engineering or technical deployment experience that includes customer-facing work.You had first experience of leading a technical customer-facing team of 3x direct reports.You have strong technical background, preferred in fields such as Computer Science, Mathematics, Software Engineering, Physics, and Data Science.You can write and review production-grade code using Python and SQL. You possess a strong understanding of REST APIs.You excel at breaking down complex problems and making quick, well-informed decisions even under pressure.You build strong relationships with both technical and business stakeholders at all levels, driven by curiosity and a customer-centric mindset that helps you understand their needs and solve their challenges.You are creative and proactive, always seeking new ways to deliver value and stand out with customers.You are collaborative and work well with your peers in product teams, engineers and other GTM teams.You are humble and have a growth mindset, with a willingness to learn new skills and methodologies and bring best practices into our business.You have excellent written and spoken English.You are open to a hybrid work model and can work from our NYC office at least three days per weekIdeal Qualifications (but not required)You have 8+ years of experience as a Forward Deployed Engineer, Solution Engineer, Implementation Specialist or an equivalent position within a B2B SaaS company.You have led a large technical customer facing team of 5-10 direct reports, have experience in hiring and retaining exceptional talent.You have experience in building AI applications.You have experience in applying and optimizing statistical and machine learning models to solve business problems.You have experience with at least one of the major cloud platforms (AWS, Azure, GCP).You are fluent in Spanish and/or Portuguese.What We OfferWork with colleagues that lift you up, challenge you, celebrate you and help you grow. We come from many different backgrounds, but what we have in common is the desire to operate at the very top of our fields. If you are similarly capable, caring, and driven, you'll find yourself at home here.Make an impact and meaningfully shape an early-stage company.Experience a truly flat hierarchy and communicate directly with founding team members. Having an opinion and voicing your ideas is not only welcome but encouraged, especially when they challenge the status quo.Learn from experienced mentors and achieve tremendous personal and professional growth. Get to know and leverage our network of leading tech investors and advisors around the globe.Receive a top-of-market equity and cash compensation package.Get access to a self-development budget you can use to e.g. attend conferences, buy books or take classes.Use the equipment of your choice including meaningful home office set-up.Our StanceWe're eager to meet talented and driven candidates regardless of whether they tick all the boxes. We're looking for someone who will add to our culture, not just fit within it. We strongly encourage individuals from groups traditionally underestimated and underrepresented in tech to apply.We seek to actively recognize and combat racism, sexism, ableism and ageism. We embrace and support all gender identities and expressions, and celebrate love in its many forms. We won't inquire about how you identify or if you've experienced discrimination, but if you want to tell your story, we are all ears.About UsTaktile is building the world's leading software platform for running critical and highly-automated decisions. Our customers use our product to catch fraudsters, prevent money laundering, and expand access to credit for small businesses, among many other use cases. Taktile is already making millions of such decisions across the globe every day.Taktile is based in Berlin, London and New York City. It was founded by machine learning and data science veterans with extensive experience building and running production ML in financial services. Our team consists of engineers, entrepreneurs, and researchers with a diverse set of backgrounds. Some of us attended top universities such as Harvard, Oxford, and Stanford and some of us have no degree at all. We have accumulated extensive work experience at leading tech companies, startups, and the enterprise software sphere.Our backers include Y Combinator, Index Ventures, and stellar angels such as the founders of Looker, GitHub, Mulesoft, Datadog and UiPath.
Machine Learning Engineer
Data Science & Analytics
Software Engineer
Software Engineering
Solutions Architect
Software Engineering
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H Company.jpg

Member of technical staff (Data Research)

H Company
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FR.svg
France
GB.svg
United Kingdom
Full-time
Remote
false
About H: H exists to push the boundaries of superintelligence with agentic AI. By automating complex, multi-step tasks typically performed by humans, AI agents will help unlock full human potential.H is hiring the world’s best AI talent, seeking those who are dedicated as much to building safely and responsibly as to advancing disruptive agentic capabilities. We promote a mindset of openness, learning, and collaboration, where everyone has something to contribute. About the Team: The AI Data team advances the performance of Large Language Models (LLMs) and Vision-Language Models (VLMs) through cutting-edge data-centric techniques. From synthetic data generation to model distillation and AI-driven preference alignment, we develop high-quality datasets that enhance model efficiency, reasoning, and adaptability. Our work directly impacts the training and fine-tuning of frontier AI systems, ensuring they learn from richer, more diverse, and better-structured data.Join us in shaping the future of AI through cutting-edge data optimization. We’re looking for driven individuals who thrive in fast-changing environments, adapt to new research paradigms, and eagerly take on challenges—whether deploying models, inspecting data, or pioneering new synthetic and reinforcement learning data methods.Key Responsibilities:Develop and implement cutting-edge data strategies to improve the performance, efficiency, and applicability of LLMs, VLMs and Action Models:Generate and augment synthetic multimodal datasets, including images, text, and action trajectories, to advance model capabilities in areas like VQA, agent behaviors, and virtual navigationApply model distillation techniques to optimize large-scale models for edge deployment, ensuring scalability without compromising performanceDesign and iterate on evaluation frameworks to target edge cases and measure model improvements across multiple domainsLead research into aligning data with human and AI preferences, implementing feedback loops to refine agent decision-making and learning behaviorsCollaborate effectively with cross-functional teams to integrate data-driven solutions into LLM, VLM and Agent systemsStay at the forefront of breakthroughs in AI data strategies, model distillation, and multimodal learning through active scientific explorationRequirements:Technical skills:Strong, polyvalent programming skills in Python covering parallel computing, system design, large-scale deployments, AWS deployments and model evaluationsExperience developing and maintaining multimodal data pipelinesExperience in training and deploying LLMs, VLMs or Pytorch modelsResearch skills:MSc or PhD in machine learning, computer vision, natural language processing, or a related fieldDeep understanding of training and evaluation paradigms for multimodal modelsSoft skills:Strong communication skills with technical and non-technical staffEffectiveness in fast-changing environmentsNice to Have:Experience with agent-specific data pipelines and improvement techniques is a plusExperience managing efficient multi-modal human annotation platforms is a plusLocation:Paris or London.This role is hybrid, and you are expected to be in the office 3 days a week on average.Please expect some travel between offices on a reasonable cadence (e.g., every 4-6 weeks).What We Offer:Join the exciting journey of shaping the future of AI, and be part of the early days of one of the hottest AI startupsCollaborate with a fun, dynamic and multicultural team, working alongside world-class AI talent in a highly collaborative environmentEnjoy a competitive salaryUnlock opportunities for professional growth, continuous learning, and career developmentIf you want to change the status quo in AI, join us.
Machine Learning Engineer
Data Science & Analytics
Data Engineer
Data Science & Analytics
Research Scientist
Product & Operations
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H Company.jpg

Member of technical staff (Models)

H Company
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FR.svg
France
GB.svg
United Kingdom
Full-time
Remote
false
About H: H exists to push the boundaries of superintelligence with agentic AI. By automating complex, multi-step tasks typically performed by humans, AI agents will help unlock full human potential.H is hiring the world’s best AI talent, seeking those who are dedicated as much to building safely and responsibly as to advancing disruptive agentic capabilities. We promote a mindset of openness, learning, and collaboration, where everyone has something to contribute. About the Team: The Models team builds the foundational models that power our cutting-edge agentic technology. We focus on training techniques to optimize model capabilities specifically for agent applications. This allows us to achieve the best performance at a given inference cost. Our work spans the development of Large Language Models (LLMs) and Vision-Language Models (VLMs), enabling agents to perceive, understand, and act within complex environments. We are deeply involved in enhancing these models through training methods with a focus on improved instruction following, tool use, and interaction with dynamic environments via large-scale reinforcement learning and reward modeling. We operate at the intersection of research and product, translating cutting-edge research into practical solutions that drive the next generation of AI. We are looking for bright, motivated individuals to join our ranks and shape the future of superintelligent AI.Key Responsibilities:Develop and train advanced LLMs and VLMs, including multimodal architecturesResearch and implement training methods for enhanced capabilities like instruction following and tool useDesign and optimize data pipelines and training systems for large-scale distributed trainingCollaborate with cross-functional teams to integrate models into agentic AI systemsEvaluate model performance and communicate findings to stakeholdersStay current with advancements in LLMs, VLMs, and related fieldsRequirements:Technical skills:Strong programming skills (Python, Git)Expertise in deep learning frameworks (PyTorch, JAX, TensorFlow)Experience with large-scale distributed training of LLMs and VLMsHands-on experience with LLM training, alignment, and reinforcement learningKnowledge of multimodal architectures and applicationsResearch skills:Publications in top-tier AI conferences (e.g., NeurIPS, ICML, CVPR, ACL, ICCV)Advanced degree (PhD or MSc) in a relevant field (e.g., ML, DL, NLP, CV)Soft skills:Excellent communication and presentation skillsStrong collaboration and teamwork skillsPassion for AI and problem-solvingBonuses:Industry experienceExperience in LLM training with RLExperience with data processing techniquesLocation:Paris or London.This role is hybrid, and you are expected to be in the office 3 days a week on average.Please expect some travel between offices on a reasonable cadence (e.g., every 4-6 weeks).What We Offer:Join the exciting journey of shaping the future of AI, and be part of the early days of one of the hottest AI startupsCollaborate with a fun, dynamic and multicultural team, working alongside world-class AI talent in a highly collaborative environmentEnjoy a competitive salaryUnlock opportunities for professional growth, continuous learning, and career developmentIf you want to change the status quo in AI, join us.
Machine Learning Engineer
Data Science & Analytics
Computer Vision Engineer
Software Engineering
NLP Engineer
Software Engineering
Research Scientist
Product & Operations
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Console.jpg

Applied AI Engineer

Console
USD
0
200000
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350000
US.svg
United States
Full-time
Remote
false
About UsConsole is an AI platform that automates IT and internal support. We help companies scale without scaling headcount, and give employees instant resolution to their issues. Our agents understand the full context of the organization, handle requests end-to-end and pull in humans only when necessary.Today, companies like Ramp, Scale, Webflow, and Flock Safety rely on Console to automate over half of their IT & HR requests. We've won every bake-off against our competitors, closed every trial customer and expect to 10x usage by year-end.We're a small, talent-dense team: naturally curious, high-agency and low-ego. Our organization is very flat and ideas win on merit, not hierarchy. We're hiring exceptional people to keep up with demand. We're backed by Thrive Capital and world-class angels.About the roleAs an Applied AI Engineer at Console, you’ll work on the core agent loop and the many AI flows that make our product feel like magic. You will work closely with the product team and leadership to ship experiences which delight users and "just work".Some examples of work you might do:Building a copilot agent that human agents can delegate work to and get 10x more doneArchitecting product flows that collect user feedback and feed into online evals for rapid iterationLearning from unresolved tickets and suggesting new automations to customers automaticallyYou'll have room to be creative, own projects end-to-end, and shape both the platform and the product vision.This role is based in San Francisco, CA. We work in-person and offer relocation assistance to new employees.About youYou're a product builder with strong generalist technical skills, and you know how to maximize your impact to deliver great experiences for users and customersYou have great taste; you understand that the best AI experiences feel great to use and you care deeply about getting the details rightYou carefully study data to discover qualitative insights from individual traces and can build quantitative systems to evaluate performance at scaleYou're immersed in the world of frontier AI and constantly learning about effective AI architectureYou've worked on AI systems with real usage and know how to iterate effectively on production agentsRequirements4+ years of full-time software engineering experience, with a recent focus on applied AI product engineeringComfortable working and contributing across the entire stack (Typescript/Node/React)Obsessed with building incredible product experiences for users, and never happy with "good enough"Why join Console?Product-market fit: We have built the leading product in our category, in a massive market. We've hit an inflection point and are on track to build a generational company. World-class team: We seek high agency contributors who are comfortable navigating ambiguity, ruthlessly prioritize what matters and are action-biased.Grow with us: We reward impact, not credentials or years of experience. We intend to grow talent from within as we scale up.Competitive pay and benefits: top compensation with full benefits including:Equity with early exercise & QSBS eligibilityComprehensive health, dental, and vision insuranceUnlimited PTO401(k)Meals provided daily in office
Machine Learning Engineer
Data Science & Analytics
Software Engineer
Software Engineering
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Faculty.jpg

Technical Director - Financial Services

Faculty
0
0
-
0
GB.svg
United Kingdom
Full-time
Remote
false
About Faculty At Faculty, we transform organisational performance through safe, impactful and human-centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.We're looking for a Technical Director to join our Professional and Financial Services business unit. This is a new, senior-level position created due to rapid growth and increased demand. The ideal candidate will be an established technology leader with a strong background in AI and machine learning, particularly within the financial services sector. You will balance technical expertise with commercial and strategic leadership, driving the development and delivery of high-caliber AI solutions for our clients, which include banks, asset managers, insurers, and law firms. Your role will be to lead and mentor a team of world-class data scientists and machine learning engineers, and you will work with the business unit leadership to develop a differentiated technical vision for the business unit.What you'll doTechnical Leadership and DeliveryProvide hands-on technical guidance for complex, high-priority projects (40% of your time).Lead the development and delivery of advanced AI solutions and ensure technical excellence across the business unit.Advise on solution architecture, advanced modelling and engineering best practices.Identify and implement new tools and processes to enhance delivery quality.Team Leadership and StrategyDefine and champion the technical vision for our professional and financial services clients.Lead recruiting, team structure, and professional development for technical staff.Collaborate with the Business Unit Director on commercial strategy and project resourcing.Business DevelopmentAct as a technical authority in client meetings to secure and expand market opportunities.Create and share technical thought leadership through conferences, articles, and other media.Identify new market opportunities and technologies.Who we're looking forAn experienced technology leader with a track record of successfully leading AI/ML strategy and project delivery.Strong understanding of MLOps, with experience deploying commercially valuable AI applications in financial services.Experience leading full-stack technology teams, with a solid grasp of systems architecture and engineering fundamentals.Knowledge of the financial services landscape, including commercial drivers and the ability to articulate how AI can accelerate business outcomes.Strong communication skills, with the ability to explain complex technical information to both internal and external stakeholders.A proven interest in and ability to mentor and develop team members.A pragmatic and outcome-focused mindset, balancing big-picture strategy with real-world execution. What we can offer you: The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.
Machine Learning Engineer
Data Science & Analytics
Software Engineer
Software Engineering
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Senior Machine Learning Operations Engineer

Zeromark
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US.svg
United States
Full-time
Remote
false
About UsZeromark builds AI-driven counter-drone systems that actually work in combat. No PowerPoints. No hype. Just field-proven technology that saves lives.We've doubled year-over-year for two straight years, winning contracts that prove what we've always known: real innovation happens in the dirt, not in conference rooms. Our systems transform standard weapons into AI-powered platforms that detect, track, and neutralize drone threats—because a $200 drone shouldn't require a million-dollar countermeasure.Here's what makes us different: ZeroMark operators don't build from behind screens. You'll validate tech from Blackhawk helicopters, train alongside Tier-1 units (who happen to be our coworkers), and test at legendary ranges from White Sands to the cliffs of Hawaii. When we say field-tested, we mean you'll shoot it, fly with it, and push it to failure. We don't tweet about changing the world—we're too busy actually doing it. Dark humor required, thick skin recommended.If you want to make an actual impact—and have some unforgettable Tuesday afternoons along the way—let's talk. We're all about delivering practical, field-tested tech, not just theories.The RoleWe are seeking a highly skilled and experienced Senior Machine Learning Generalist to join our talented team. This individual will play a crucial role in designing, developing, and deploying machine learning models across various defense applications. You will work closely with both our general software engineering team and our computer vision engineering team, bridging the gap between foundational software development and advanced computer vision applications. This role requires a strong understanding of diverse ML techniques, excellent problem-solving abilities, and the capacity to adapt to evolving project needs.ResponsibilitiesDesign, develop, and implement end-to-end machine learning pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment.Collaborate with the general software engineering team to integrate ML models into existing software systems and ensure scalability and maintainability.Work in conjunction with computer vision specialists to apply and optimize ML techniques for image and video analysis, object detection, tracking, and recognition in defense contexts.Research and evaluate new machine learning algorithms, tools, and technologies to enhance our capabilities and solve challenging problems.Perform rigorous model testing, validation, and performance tuning to ensure robustness and accuracy in real-world scenarios.Contribute to the development of best practices for ML engineering, including MLOps, version control, and reproducible research.Mentor junior engineers and contribute to a culture of continuous learning and knowledge sharing.Communicate technical concepts effectively to both technical and non-technical stakeholders.QualificationsEducation: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.Experience: 5+ years of experience in machine learning engineering, with a proven track record of deploying ML models in production environments.Technical Skills:Strong proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).Solid understanding of core machine learning concepts, including supervised, unsupervised, and reinforcement learning.Experience with various machine learning model architectures and their application (e.g., CNNs, RNNs, Transformers, decision trees, support vector machines).Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).Experience with MLOps tools and practices.Experience deploying a variety of edge systems.Experience with TensorRT and other similar technologies.Deep knowledge of C++ and Python.Domain Knowledge:Experience or strong interest in defense, aerospace, or related industries is highly desirable.Understanding of the unique challenges and considerations for deploying ML in defense applications (e.g., adversarial robustness, real-time constraints, data security).Collaboration & Communication:Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.Ability to translate complex technical concepts into clear and concise language.Problem-Solving:Strong analytical and problem-solving skills, with a proactive and innovative approach.Ability to work independently and manage multiple priorities in a fast-paced environment.Preferred QualificationsExperience with specific computer vision tasks such as object detection, segmentation, or tracking.Familiarity with real-time ML systems and embedded systems.Contributions to open-source projects or publications in relevant fields.
Machine Learning Engineer
Data Science & Analytics
DevOps Engineer
Data Science & Analytics
Computer Vision Engineer
Software Engineering
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Senior Field AI Engineer - Canada (Remote)

Fiddler AI
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CA.svg
Canada
Full-time
Remote
true
Our PurposeAt Fiddler, we understand the implications of AI and the impact that it has on human lives. Our company was born with the mission of building trust into AI. With the rise of the internet, trust in AI has been degraded by a plethora of issues like spam, fraudulent transactions, hate speech, and online abuse. Fiddler enables organizations to get ahead of these issues by building trustworthy, transparent, and explainable AI solutions. Fiddler partners with AI-first organizations to help build a long-term framework for responsible AI practices, which, in turn, builds trust with their user base. Data Science, MLOps, and business teams use Fiddler AI to monitor, explain, analyze, and improve their AI solutions to identify performance gaps, mitigate bias, and drive better outcomes. Our platform enables engineering teams and business stakeholders alike to understand the “why” and how behind model outcomes.  Our FoundersFiddler AI is founded by Krishna Gade (engineering leadership at Facebook, Pinterest, Twitter, and Microsoft) and Amit Paka (two-time founder with acquisitions by Samsung and PayPal and product roles at Expedia and Microsoft). We are backed by Insight Partners, Lightspeed Venture Partners, and Lux Capital. Why Join UsOur team is motivated to unlock the AI opaque box and help society harness the power of AI. Joining us means you get to make an impact by helping reduce algorithmic bias and ensure that models in production across many different industries are transparent and ethical.  We are an early-stage startup and have a rapidly growing team of intelligent and empathetic doers, thinkers, creators, builders, and everyone in between. The AI and ML industry has a rapid pace of innovation and the learning opportunities here are monumental. This is your chance to be a trailblazer.  Fiddler is recognized as a pioneer in the field of AI Observability and has received numerous accolades, including:  2022 a16z Data50 list, 2021 CB Insights AI 100 most promising startups, 2020 WEF Technology Pioneer, 2020 Forbes AI 50 most promising startups of 2020, and a 2019 Gartner Cool Vendor in Enterprise AI Governance and Ethical Response. By joining our brilliant (at least we think so) team, you will help pave the way in the AI Observability space.What You’ll DoYou will act as a trusted advisor to our customers while also building relationships with technical stakeholdersWork alongside a Fiddler Delivery Manager to help deliver Fiddler onboarding services for our new customersYou will act as the “Voice of the Customer”; regularly engaging them on status calls, educating on product roadmap and QBRs, managing escalations, while influencing our roadmap in partnership with our Product teamBecome a Fiddler AI Observability product specialist in order to help customers utilize the platform to meet their observability needsEnsure technical success for customer onboarding by writing custom code to integrate with their data pipeline using tools like Snowflake, Airflow, MLFlow, S3, Kafka, etcDevelop Fiddler platform integration to expedite onboarding with data platforms, workflow tools, and ML platformSpearhead new opportunities in which Fiddler can provide the most value that will drive renewals and expansionWhat We’re Looking For2+ years of experience working with ML modelsFamiliarity with Kubernetes in the public Cloud environments (AWS, Azure, GCP)Knowledge of data science concepts, including developing interpretable machine learning model tools to be used in Fiddler’s productFamiliarity with tools used for structured and unstructured data like Hadoop, Snowflake, BigQuery, Spark, Kafka, Kinesis, RabbitMQ, Airflow, MLFlow, Luigi, Kubeflow, ArgoWorking knowledge of Generative AI, Large Language Models, and related concepts like agents, RAG, etc.Experience with coding, preferably in PythonExcellent organizational, communication, writing, and interpersonal skillsCuriosity, ownership, empathy towards customers, willingness to learn new things, and desire to inspire others are values we careThe posted range represents the expected salary range for this job requisition and does not include any other potential components of the compensation package and perks previously outlined. Ultimately, in determining pay, we'll consider your experience, leveling, location, and other job-related factors.Fiddler is proud to be an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you require special accommodations in order to complete the interviews or perform job duties, please inform the recruiter at the beginning of the process.Beware of job scam fraud! We prioritize candidate safety. Our recruiters use @fiddler.ai email addresses exclusively. In the US, we do not conduct interviews via text or instant message, or to provide sensitive personally identifiable information such as bank account or social security numbers. If you have been contacted by someone claiming to be from a different domain about a job offer, please report it as potential job fraud to hr@fiddler.ai.
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Applied AI Engineer & Researcher - Dallas, USA

Speechify
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US.svg
United States
Remote
true
PLEASE APPLY THROUGH THIS LINK: https://job-boards.greenhouse.io/speechify/jobs/4510121004  DO NOT APPLY BELOW The mission of Speechify is to make sure that reading is never a barrier to learning. Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its App of the Day. Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies. This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, passionate about making product decisions, and has experience building great user experiences that delight users. We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount.  Our interview process involves several technical interviews and we aim to complete them within 1 week.  What You’ll Do Researching and implementing state-of-the-art in NLP and TTS or CV with a focus on image generation Work on building the most human sounding AI speech model in the world An Ideal Candidate Should Have Experience with research and development in NLP or TTS or CV with a focus on image generation. Experience in ML Preferred: Experience deploying NLP or TTS models to production at a large scale Experience managing engineers and growing a research & development team Experience programming in Python: Tensorflow and PyTorch frameworks specifically. What We Offer A fast-growing environment where you can help shape the culture An entrepreneurial crew that supports risk, intuition, and hustle A hands-off approach so you can focus and do your best work The opportunity to make an impact in a transformative industry A competitive salary, a collegiate atmosphere, and a commitment to building a great asynchronous culture Think you’re a good fit for this job?  Tell us more about yourself and why you're interested in the role when you apply. And don’t forget to include links to your portfolio and LinkedIn. Not looking but know someone who would make a great fit?  Refer them!  Speechify is committed to a diverse and inclusive workplace.  Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Machine Learning Engineer
Data Science & Analytics
NLP Engineer
Software Engineering
Computer Vision Engineer
Software Engineering
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Applied AI Engineer & Researcher - Boston, USA

Speechify
0
0
-
0
US.svg
United States
Remote
true
PLEASE APPLY THROUGH THIS LINK: https://job-boards.greenhouse.io/speechify/jobs/4510121004  DO NOT APPLY BELOW The mission of Speechify is to make sure that reading is never a barrier to learning. Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its App of the Day. Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies. This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, passionate about making product decisions, and has experience building great user experiences that delight users. We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount.  Our interview process involves several technical interviews and we aim to complete them within 1 week.  What You’ll Do Researching and implementing state-of-the-art in NLP and TTS or CV with a focus on image generation Work on building the most human sounding AI speech model in the world An Ideal Candidate Should Have Experience with research and development in NLP or TTS or CV with a focus on image generation. Experience in ML Preferred: Experience deploying NLP or TTS models to production at a large scale Experience managing engineers and growing a research & development team Experience programming in Python: Tensorflow and PyTorch frameworks specifically. What We Offer A fast-growing environment where you can help shape the culture An entrepreneurial crew that supports risk, intuition, and hustle A hands-off approach so you can focus and do your best work The opportunity to make an impact in a transformative industry A competitive salary, a collegiate atmosphere, and a commitment to building a great asynchronous culture Think you’re a good fit for this job?  Tell us more about yourself and why you're interested in the role when you apply. And don’t forget to include links to your portfolio and LinkedIn. Not looking but know someone who would make a great fit?  Refer them!  Speechify is committed to a diverse and inclusive workplace.  Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Machine Learning Engineer
Data Science & Analytics
Research Scientist
Product & Operations
NLP Engineer
Software Engineering
Computer Vision Engineer
Software Engineering
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Speechify.jpg

AI Engineer & Researcher, Inference - Austin, USA

Speechify
-
US.svg
United States
Remote
true
PLEASE APPLY THROUGH THIS LINK: https://job-boards.greenhouse.io/speechify/jobs/5287658004  DO NOT APPLY BELOW The mission of Speechify is to make sure that reading is never a barrier to learning. Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its App of the Day. Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies. This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, passionate about making product decisions, and has experience building great user experiences that delight users. We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount.  Our interview process involves several technical interviews and we aim to complete them within 1 week.  What You’ll Do Work alongside machine learning researchers, engineers, and product managers to bring our AI Voices to their customers for a diverse range of use cases Deploy and operate the core ML inference workloads for our AI Voices serving pipeline Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our deployed models Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues An Ideal Candidate Should Have Experience shipping Python-based services Experience being responsible for the successful operation of a critical production service Experience with public cloud environments, GCP preferred Experience with Infrastructure such as Code, Docker, and containerized deployments. Preferred: Experience deploying high-availability applications on Kubernetes. Preferred: Experience deploying ML models to production What We Offer A dynamic environment where your contributions shape the company and its products A team that values innovation, intuition, and drive Autonomy, fostering focus and creativity The opportunity to have a significant impact in a revolutionary industry Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain Think you’re a good fit for this job?  Tell us more about yourself and why you're interested in the role when you apply. And don’t forget to include links to your portfolio and LinkedIn. Not looking but know someone who would make a great fit?  Refer them!  Speechify is committed to a diverse and inclusive workplace.  Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Machine Learning Engineer
Data Science & Analytics
Software Engineer
Software Engineering
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AI Engineer & Researcher, Inference - San Francisco, USA

Speechify
-
No items found.
Remote
true
PLEASE APPLY THROUGH THIS LINK: https://job-boards.greenhouse.io/speechify/jobs/5287658004  DO NOT APPLY BELOW The mission of Speechify is to make sure that reading is never a barrier to learning. Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its App of the Day. Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies. This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, passionate about making product decisions, and has experience building great user experiences that delight users. We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount.  Our interview process involves several technical interviews and we aim to complete them within 1 week.  What You’ll Do Work alongside machine learning researchers, engineers, and product managers to bring our AI Voices to their customers for a diverse range of use cases Deploy and operate the core ML inference workloads for our AI Voices serving pipeline Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our deployed models Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues An Ideal Candidate Should Have Experience shipping Python-based services Experience being responsible for the successful operation of a critical production service Experience with public cloud environments, GCP preferred Experience with Infrastructure such as Code, Docker, and containerized deployments. Preferred: Experience deploying high-availability applications on Kubernetes. Preferred: Experience deploying ML models to production What We Offer A dynamic environment where your contributions shape the company and its products A team that values innovation, intuition, and drive Autonomy, fostering focus and creativity The opportunity to have a significant impact in a revolutionary industry Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain Think you’re a good fit for this job?  Tell us more about yourself and why you're interested in the role when you apply. And don’t forget to include links to your portfolio and LinkedIn. Not looking but know someone who would make a great fit?  Refer them!  Speechify is committed to a diverse and inclusive workplace.  Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Machine Learning Engineer
Data Science & Analytics
Software Engineer
Software Engineering
DevOps Engineer
Data Science & Analytics
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