Find AI Work That Works for You

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Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 60 health plans, including many of the top 20, and representing more than 160 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.Machinify builds machine learning models for some of the largest health plans in the country to identify nearly $1B in erroneous healthcare payments. Our customers receive tens of millions of claims each year, many of which are billed with mistakes or fraud. Our production models detect and stop those errors on a daily basis, resulting in measurable healthcare savings that significantly outperform industry standards. Machinify has already had a huge impact as a small company, and we are growing quickly!We are looking for a Data Scientist | ML for our "Pay" team (claims payments product) to advance our models further. In addition to building best-in-class models, this person will create technical frameworks and tools to help the team achieve greater scale and improved business outcomes.What You’ll Do:Master understanding of various claims payment policies and healthcare concepts.Build and improve the models by thoughtfully curating data and creating features.Precisely measure and improve model performance against real-world outcomes. Make operational recommendations to the customer to optimize model results. Interpret and refine large-scale data created by complex business workflows.Advance the team’s capabilities by improving pipelines, infrastructure, and tools. What You’ll Bring:Several years of experience solving real-world business problems with data and ML modelingProven ability to make team-level contributions and develop frameworks and tools to improve the work of manyAble to build a high-level, strategic work plan while keeping attention to detailExperience precisely measuring and optimizing the business impact of your workExperience handling large-scale, complex data which may not be clean or well-definedExperience writing production-quality code (i.e. building pipelines, productionizing models) and overcoming practical challenges to deploy a modelDeep curiosity about healthcareEqual Employment Opportunity at MachinifyMachinify is committed to hiring talented and qualified individuals with diverse backgrounds for all of its positions. Machinify believes that the gathering and celebration of unique backgrounds, qualities, and cultures enriches the workplace. See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/

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About Enterpret Enterpret is redefining how businesses understand and act on customer feedback. We are building an AI-native platform that centralises feedback from every source surveys, reviews, support tickets, communities and turns it into clear, actionable insights that drive business growth. We are trusted by some of the world’s most customer-obsessed companies like Canva, Descript, Notion, Perplexity and many more, and backed by leading investors like Kleiner Perkins, Canaan Partners, and Peak XV Partners. Our mission: to unlock the voice of the customer for every product team on the planet. About the Role This is a hands-on role for someone who’s equally strong in research thinking and engineering execution. You will define what “good” looks like for AI-powered features, build systems that meet that bar, and own them through launch and beyond. From writing eval plans to debugging failures in production, you will work across the stack and across functions to ship reliable, high-quality LLM-driven systems. What You Will Do ? You will design, build & ship AI-backed features that are reliable in production Define the quality bar: design eval rubrics, test plans, and rollout criteria. Make sure they’re measurable and enforced. Build with real-world constraints: write and extend production code, set up monitoring, and add tests that catch regressions before users do. Own features end to end from problem framing to modeling, from system design to rollout and iteration. Debug failures across the stack including data, infra, model, prompt logic and harden the system with what you learn. Design and implement systems: retrieval pipelines, agents, or hybrid patterns, based on what the problem actually needs. Work across functions: collaborate with product, infra, and engineers to ship features that actually stick. What It Takes ? You have built and shipped AI systems before and carried the load when things broke post-launch. Strong research instincts: you are good at defining what “working” means and designing evaluations that reflect real-world usage. Solid engineering skills: you write clean, testable Python, debug at system boundaries, and know your way around production stacks. LLM understanding: you have worked with modern models and know how to prompt, fine-tune, or wrap them with tooling and evaluation. Systems mindset: you think in interfaces, data contracts, failure modes, and rollout plans, not just model tweaks. Practical bias: you care more about what ships and survives than what’s novel. Ownership: you take initiative, communicate clearly, and push for quality without being asked. Why Enterpret? We build AI systems that people can trust because they have been tested, monitored, and hardened through real usage. We care deeply about quality. Eval plans, incident retros, and per-tenant guardrails aren't checkboxes, they're the core of how we build. We believe research belongs in production, not just papers. You will see your ideas live in running systems within weeks, not years. We are small enough that every engineer matters, and focused enough that there's no busywork, just high-impact problems. You will be part of a team that runs toward hard, ambiguous challenges and sees them through to working, reliable systems. There is no playbook here, we are writing it as we go. If that excites you, not scares you, you will thrive here.  

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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 700+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started.Role OverviewWe’re hiring a Senior Marketing Data Scientist to partner closely with Harvey’s Marketing organization and build our marketing data science function from the ground up. In this role, you’ll serve as a trusted analytical partner to Marketing, GTM, and Finance - defining how we measure marketing success, understanding what drives channel and campaign performance, and informing where and how we invest to accelerate growth. As one of the earliest Marketing data science hires, you’ll own the development of core Marketing metrics, scalable dashboards, and analytical frameworks that enable data-driven decision-making across the business.What You’ll DoEmbed deeply with the Marketing organization as a trusted partner, identifying opportunities to improve performance and drive growth.Define, track, and evolve core metrics across marketing and business functions, building scalable dashboards and reporting frameworks that enable data-driven decision-making.Design, implement, and evaluate models (multi-touch attribution, marketing mix modeling, incrementality) for comprehensive Marketing Channel and Campaign performance and contribution.Apply statistical and machine learning techniques to model user behavior, forecast trends, and identify opportunities for growth and optimization.Translate complex analyses into compelling stories, delivering clear recommendations to cross-functional partners and executives.Partner with Marketing, RevOps and GTM System, to co-develop data infrastructure, ensuring robust pipelines, reliable data sources, and scalable systems that power analytics and modeling.Lead cross-functional analytics initiatives that synthesize competitive dynamics, customer feedback, and market trends into actionable opportunities for the business.Champion a data-informed culture by establishing best practices, mentoring peers, and shaping the strategic role of data science at Harvey.What You Have6+ years of experience in quantitative roles operating in highly ambiguous environments, ideally as an early data scientist or Marketing analyst within a hyper-growth product company or research organizationExpertise in SQL, with extensive experience extracting large datasets and designing ETL workflowsStrong experience with modern data stack, such as DBT, Looker and OmniProficiency in quantitative programming languages, such as Python and RExperience defining, implementing, and operationalizing Marketing campaign- and channel-level metrics from the ground upStrong communication skills, with the ability to effectively partner with leaders across Marketing, GTM and FinanceStrategic mindset capable of generating insights that extend beyond traditional statistical significance testing to inform long-term product and business directionCompensation$170,000 - $200,000 USDPlease find our CA applicant privacy notice here.#LI-SB1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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🎨 OpusClip is the world's No.1 AI video agent, built for authenticity on social media.We envision a world where everyone can authentically share their story through video, with no expertise needed. Within just 18 months of our launch, over 10 million creators and businesses have used OpusClip to enhance their social presence. We have raised $50 million in total funding and are fortunate to have some of the most supportive investors, including SoftBank Vision Fund, DCM Ventures, Millennium New Horizons, Fellows Fund, AI Grant, Jason Lemkin (SaaStr), Samsung Next, GTMfund, Alumni Ventures, and many more. Check out our latest coverage by Business Insider featuring our product and funding milestones, and our recognition as one of The Information's 50 Most Promising Startups in 2024. Headquartered in Palo Alto, we are a team of 100 passionate and experienced AI enthusiasts and video experts, driven by our core values: Be a Champion Team Prioritize Ruthlessly Ship fast, Quality Follows Obsess over customers Be a part of this exciting journey with us!📝 Your ResponsibilityAI System Architecture: Design and build scalable, low-latency AI inference microservices. You will move beyond simple scripts to architecting robust systems that handle high-volume video processing.Engineering-First Model Deployment: Collaborate with the team to build production pipelines for Video Understanding and LLMs. You will be responsible not just for the model's accuracy, but for its throughput, cost-efficiency, and integration into the core backend.High-Standard "Vibe Coding": We embrace AI-assisted coding (Cursor, Copilot, etc.), but we demand engineering rigor. You are responsible for ensuring all code—whether written by you or generated by AI—is modular, type-safe, thoroughly tested, and maintainable.Performance Optimization: Profile and optimize Python/C++ code and model inference layers (e.g., quantization, batching, caching strategies) to minimize GPU costs and user wait time.R&D to Production: Conduct research on cutting-edge LLMs/multimodal models and rapidly refactor experimental code into stable, production-ready features.📝 QualificationsBachelor's degree or above in Computer Science or related fields.3+ years of work experience (Fresh graduates with strong internships/project experience are welcome).Strong System Design Sense: Understanding of distributed systems, API design (REST/gRPC), asynchronous processing (task queues like Celery/Redis), and database interactions.Solid Engineering Fundamentals:Fluent in Python (C++ or JavaScript is a plus).Ability to write clean, SOLID, and testable code.Proficiency with Docker/Containerization and CI/CD workflows.AI/ML Proficiency:Proficient in PyTorch or TensorFlow.Familiarity with model serving frameworks (e.g., vLLM, TGI, Triton) and ONNX.Experience in one of the below areas:Video Understanding / Computer Vision.LLM Fine-tuning / RAG Systems.Backend Systems for AI (FastAPI, Vector DBs, Microservices).Enthusiastic, excellent communicator, self-motivated, and possessing a strong sense of ownership.📝 Preferred (Bonus Points)Full-Stack AI Experience: Experience building an end-to-end product feature—from the prompt engineering layer down to the API deployment and database schema.Inference Optimization: Experience with TensorRT, quantization (AWQ/GPTQ), or FlashAttention to speed up model performance.Vector Database at Scale: Experience managing vector stores (Pinecone, Milvus, Weaviate) in a production environment.Open Source & Community: Experience building APIs/services/open-source tools with ChatGPT/OpenAI APIs.Projects completed or Research papers published in top-tier conferences (ACL, CVPR, NeurIPS, etc.).EEOOpusClip is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristics. OpusClip considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Opus Clip is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.

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🎨 OpusClip is the world's No.1 AI video agent, built for authenticity on social media.We envision a world where everyone can authentically share their story through video, with no expertise needed. Within just 18 months of our launch, over 10 million creators and businesses have used OpusClip to enhance their social presence. We have raised $50 million in total funding and are fortunate to have some of the most supportive investors, including SoftBank Vision Fund, DCM Ventures, Millennium New Horizons, Fellows Fund, AI Grant, Jason Lemkin (SaaStr), Samsung Next, GTMfund, Alumni Ventures, and many more. Check out our latest coverage by Business Insider featuring our product and funding milestones, and our recognition as one of The Information's 50 Most Promising Startups in 2024. Headquartered in Palo Alto, we are a team of 100 passionate and experienced AI enthusiasts and video experts, driven by our core values: Be a Champion Team Prioritize Ruthlessly Ship fast, Quality Follows Obsess over customers Be a part of this exciting journey with us!📝 Your ResponsibilityAI System Architecture: Design and build scalable, low-latency AI inference microservices. You will move beyond simple scripts to architecting robust systems that handle high-volume video processing.Engineering-First Model Deployment: Collaborate with the team to build production pipelines for Video Understanding and LLMs. You will be responsible not just for the model's accuracy, but for its throughput, cost-efficiency, and integration into the core backend.High-Standard "Vibe Coding": We embrace AI-assisted coding (Cursor, Copilot, etc.), but we demand engineering rigor. You are responsible for ensuring all code—whether written by you or generated by AI—is modular, type-safe, thoroughly tested, and maintainable.Performance Optimization: Profile and optimize Python/C++ code and model inference layers (e.g., quantization, batching, caching strategies) to minimize GPU costs and user wait time.R&D to Production: Conduct research on cutting-edge LLMs/multimodal models and rapidly refactor experimental code into stable, production-ready features.📝 QualificationsBachelor's degree or above in Computer Science or related fields.3+ years of work experience (Fresh graduates with strong internships/project experience are welcome).Strong System Design Sense: Understanding of distributed systems, API design (REST/gRPC), asynchronous processing (task queues like Celery/Redis), and database interactions.Solid Engineering Fundamentals:Fluent in Python (C++ or JavaScript is a plus).Ability to write clean, SOLID, and testable code.Proficiency with Docker/Containerization and CI/CD workflows.AI/ML Proficiency:Proficient in PyTorch or TensorFlow.Familiarity with model serving frameworks (e.g., vLLM, TGI, Triton) and ONNX.Experience in one of the below areas:Video Understanding / Computer Vision.LLM Fine-tuning / RAG Systems.Backend Systems for AI (FastAPI, Vector DBs, Microservices).Enthusiastic, excellent communicator, self-motivated, and possessing a strong sense of ownership.📝 Preferred (Bonus Points)Full-Stack AI Experience: Experience building an end-to-end product feature—from the prompt engineering layer down to the API deployment and database schema.Inference Optimization: Experience with TensorRT, quantization (AWQ/GPTQ), or FlashAttention to speed up model performance.Vector Database at Scale: Experience managing vector stores (Pinecone, Milvus, Weaviate) in a production environment.Open Source & Community: Experience building APIs/services/open-source tools with ChatGPT/OpenAI APIs.Projects completed or Research papers published in top-tier conferences (ACL, CVPR, NeurIPS, etc.).EEOOpusClip is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristics. OpusClip considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Opus Clip is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.

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About the teamOpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.About the roleWe are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.This role is based in Munich. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.In this role you willDesign and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.You might thrive in this role if youBring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the teamOpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development.About the role As an FDE manager, you’ll lead FDEs through high-stakes, ambiguous customer deployments and own technical and business value outcomes end to end. You’ll grow a team that can operate under pressure and help OpenAI learn from the field.You’ll partner closely with Product, Research, Sales, and GTM to ensure fieldwork informs roadmap priorities, drives new exploration, and supports safe deployment at scale. Your decisions will influence how OpenAI is trusted by the customers closest to our deployment work. Your success will be measured by how consistently your team ships, how clearly you deliver signal to Research and Product, and how durable your team and delivery model prove to be.This role is based in New York City. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. This role also will require travel up to 25%.In this role you willLead and grow a team of FDE delivering production systems with frontier modelsOwn end-to-end delivery outcomes through clarity, speed, tight coordination, and technical qualityCodify what works into tools, playbooks, and roadmap inputs that create leverage for both OpenAI and our wider developer communityNotice early indicators and raise them with urgency, whether in product behavior, customer environments, or delivery practicesUse judgement to distinguish what requires action and what does notSet a high bar for FDE performance and support each person’s growth through direct, actionable feedbackDefine how we staff and support field teams that can scale without added complexityYou might thrive in this role if youBring 8+ years of engineering or technical delivery experience, including 2+ years managing high-performing FDE or customer-facing engineersHave led high-pressure technical projects from prototype to productionWrite and review production-grade code across frontend and backend using Javascript or PythonSimplify complex work and make fast, sound decisions under pressureElevate team performance through clarity, not processOperate with urgency in ambiguous or evolving environmentsTranslate field experience into sharp, actionable feedback for Product and ResearchBuild deep trust with your team by modeling calm, focus, and judgment when it matters mostAbout OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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🚀 About WRITERWRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI.Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI.📐 About the roleAs a customer AI architect at WRITER, you'll be at the forefront of expanding human capacity through superintelligence. This isn't just a technical role; it's a deeply influential one where you'll partner directly with our leading enterprise customers. Your expertise will be crucial in uncovering their unique business challenges and architecting AI-powered solutions that leverage our powerful platform and enterprise-grade LLMs. You'll transform complex needs into tangible, high-impact applications, creating champions and driving tangible business results. Your builder's mentality and passion for bringing cutting-edge AI into the hands of real users will directly shape the future of work for some of the world's largest companies.This is a critical role that directly impacts our customers' success and product evolution. You'll contribute significantly to WRITER's mission, working with a dynamic team to push the boundaries of what's possible with generative AI.This is a hybrid role based out of our San Francisco or New York City hubs, or remote within the US. You'll initially report to our VP of technical delivery.🦸🏻‍♀️ What you'll doPartner deeply with enterprise customers to identify strategic AI use cases, validating technical feasibility and owning the end-to-end implementation of tailored solutionsArchitect and deliver custom applications, templates, and integrations leveraging WRITER's platform, APIs, and Knowledge Graph capabilities to solve complex business challengesTranslate intricate technical concepts and platform capabilities into clear, prescriptive solution recommendations, guiding customers through the generative AI landscapeCollaborate relentlessly with internal Product and Engineering teams, providing crucial customer feedback that directly influences our product roadmap and drives continuous innovationDrive down customer time-to-value by developing scalable processes, robust documentation, and efficient workflows for technical integrationsChampion the successful adoption and expansion of WRITER's AI solutions within customer accounts, ensuring maximum impact and return on investment⭐️ What you needOver 5 years of hands-on experience in technical SaaS roles, with at least 3 years specifically in solutions architecture, technical consulting, or technical account managementDeep technical fluency in Python and extensive experience leveraging APIs, especially in designing sophisticated prompts and understanding linguistic principles for AI applicationsProven track record of architecting and delivering complex technical solutions for Fortune 500 enterprises in a fast-paced, high-growth B2B SaaS environmentExceptional communication and executive presence, capable of simplifying complex AI concepts for diverse audiences, from technical teams to C-suite leadershipA true builder's mindset with a passion for emerging technologies, always eager to experiment, learn, and iterate in the rapidly evolving world of generative AIA relentless drive to Connect with customers and internal teams, Challenge the status status quo with innovative solutions, and Own the successful outcomes for our most strategic accounts 🍩 Benefits & perks (US Full-time employees)Generous PTO, plus company holidaysMedical, dental, and vision coverage for you and your familyPaid parental leave for all parents (12 weeks)Fertility and family planning supportEarly-detection cancer testing through GalleriFlexible spending account and dependent FSA optionsHealth savings account for eligible plans with company contributionAnnual work-life stipends for:Wellness stipend for gym, massage/chiropractor, personal training, etc.Learning and development stipendCompany-wide off-sites and team off-sitesCompetitive compensation, company stock options and 401kWRITER is an equal-opportunity employer and is committed to diversity. We don't make hiring or employment decisions based on race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other basis protected by applicable local, state or federal law. Under the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.By submitting your application on the application page, you acknowledge and agree to WRITER's Global Candidate Privacy Notice.

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🚀 About WRITERWRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through super intelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI.Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI.📐 About the roleWRITER is looking for a pioneering forward deployed engineer with strong software engineering and AI expertise to be embedded onsite with a strategic enterprise client as their dedicated technical partner. At WRITER, we believe in using the power of AI to unlock the potential of the enterprise. With the help of our Forward deployed engineers, we ensure our most complex enterprise clients successfully deploy and maintain the WRITER AI platform as is with the standard release configurations, and obtain any internal client-specific security and compliance approvals without compromising standard features.As a forward deployed engineer at WRITER, you'll be embedded onsite at the client location in NYC, working shoulder-to-shoulder with their engineering, AI Center of Excellence (COE), and business teams on a daily basis. This is a full-time role that requires being present at the client's office 4-5 days per week. You'll serve as the technical bridge between WRITER and the client, owning the client-specific release workflow from sandbox deployment through production. Your daily collaboration with client teams will ensure seamless integration, rapid issue resolution, and successful adoption of WRITER's AI capabilities across the organization. You will report to the head of customer solutions engineering.This is a unique opportunity to be the face of WRITER's technical excellence, building deep relationships with client stakeholders while solving complex AI deployment challenges in a fast-paced enterprise environment. If you're passionate about enterprise AI deployment, thrive in client-facing roles, and love being embedded in complex technical environments, then we want to hear from you.This role requires being onsite 2-3 days per week and travel to client location based on need. 🦸🏻‍♀️ What you'll doServe as WRITER's embedded technical AI specialist onsite, building strong daily relationships with client engineering, AI COE, and business teams, and acting as the primary point of contact for all WRITER-related technical mattersOwn the end-to-end release workflow from WRITER platform updates through production deployment across all client environments, including coordinating dual-track updates, making critical go/no-go decisions, and providing hands-on troubleshootingDesign, implement, and maintain the client's custom front-end setup, production retrieval, and agentic systems, while rigorously testing, validating, and troubleshooting AI-specific features like LLM applications, RAG performance, and prompt engineeringNavigate client security, risk, and compliance approval processes, working with Information Security teams to obtain necessary approvals, documenting compliance artifacts, and streamlining workflows to meet regulatory requirementsReduce operational pain points, contribute to long-term migration strategies for clients towards standard WRITER-managed environments, and gather real-world deployment feedback to strategically influence WRITER's product direction⭐️ What you'll need7+ years of professional experience in software engineering, with at least 5 years specifically in AI/ML development and 2+ years in highly regulated, customer-facing roles at enterprise scaleExpert-level proficiency in Python and modern JavaScript (ES6+), production software development, systems design, and modern front-end frameworks (React, Vue.js, Angular)Extensive hands-on experience deploying and optimizing LLM-based applications and agentic systems in production environments, with deep knowledge of RAG implementation, CI/CD practices for AI, and evaluating AI model performanceProven track record of managing complex multi-environment release pipelines, coordinating synchronization between distributed systems, and expertly navigating enterprise approval workflows and governance in Fortune 500 or large financial services clientsDemonstrated ability to Connect effectively with diverse client stakeholders through onsite embedding, Challenge existing technical paradigms to drive innovation, and Own problem-solving from discovery to production impact, exhibiting strong analytical, communication, and presentation skills suitable for executive engagement 🍩 Benefits & perks (US Full-time employees)Generous PTO, plus company holidaysMedical, dental, and vision coverage for you and your familyPaid parental leave for all parents (12 weeks)Fertility and family planning supportEarly-detection cancer testing through GalleriFlexible spending account and dependent FSA optionsHealth savings account for eligible plans with company contributionAnnual work-life stipends for:Wellness stipend for gym, massage/chiropractor, personal training, etc.Learning and development stipendCompany-wide off-sites and team off-sitesCompetitive compensation, company stock options and 401kWRITER is an equal-opportunity employer and is committed to diversity. We don't make hiring or employment decisions based on race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other basis protected by applicable local, state or federal law. Under the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.By submitting your application on the application page, you acknowledge and agree to WRITER's Global Candidate Privacy Notice.

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About the roleMaincode builds frontier AI models end to end. We design the models, run the infrastructure, and train on data we source and shape ourselves. What we have been calling a “data scientist” does not actually exist in the market in the form we need. The work we are doing is frontier work. It changes continuously as models, methods, and training regimes evolve, and there is no stable body of prior experience that reliably predicts success. This role is best understood internally as a Signal Engineer.The real work here is not analytics, dashboards, or big data engineering.It is about how AI models learn, and specifically how the quality, composition, timing, and structure of input signal shapes learning outcomes across the full training lifecycle, from early pre training through mid training, post training, supervised fine tuning, and reinforcement learning.The analogy we use internally is a fuels engineer for a race car. The engine matters, but performance is ultimately unlocked by obsessing over the fuel. What goes in, how it is blended, when it is introduced, and how it changes under different conditions.What you would actually doYou would be responsible for designing, sourcing, shaping, and evaluating input signal at scale so that models learn faster, learn better, and generalize more effectively.This includes:Working deeply with raw and synthetic dataDesigning new datasets and signal mixturesIterating on input distributions and formatsUnderstanding how small changes in signal affect training behaviorThinking across stages of training, not in isolationTreating data as a dynamic, evolving system rather than a static assetThis is not about knowing the right answer up front. It is about immersion, experimentation, and developing intuition through long feedback loops.The kind of person who does well hereSuccess in this role is driven almost entirely by cognitive traits and working style, not prior AI experience.People who tend to thrive here:Have extreme attention to detail and care deeply about precisionAre comfortable with long arcs of repetitive, detailed workEnjoy staring at complex, noisy information until structure emergesAre excited by tuning, blending, and calibrating inputsHave high stamina and patienceLearn new technical domains very quickly when given dense materialGet intrinsic satisfaction from incremental improvement and deep understandingThese are people who do not get bored easily. They metabolize boredom into insight. They are depth driven rather than novelty driven.We explicitly do not require prior experience with large language models or modern AI training. No one meaningfully has that experience yet. What matters is learning gradient, range, and willingness to throw yourself into the problem space.How you would workYou would spend your time inside computational environments and technical tooling.You do not need to identify as a software engineer, but you should be comfortable:Working directly with data through scripts, notebooks, and experimental pipelinesModifying existing systems and building small utilities to explore questionsUsing code as a tool for thinking, testing, and refinementThe goal is speed of learning and depth of understanding, not polish.Backgrounds that often fit wellRather than advertising this role directly, we look for people in fields that reward signal sensitivity, precision, and long horizon reasoning.We expect to see strong candidates from areas such as:Actuarial scienceForensic accounting or forensic financeQuantum computingQuantitative risk modelingApplied statistics and signal processingEconometricsOperations researchWe also see excellent fits from applied mathematics, computational physics, systems engineering, bioinformatics, reliability engineering, and similar disciplines.Many people in these fields are constrained by conservative or slow moving industries and are actively looking for something more dynamic, even if they do not yet realize there is a place for them in frontier AI.How we interviewWe are explicitly hiring for learning gradient, not recall.Our process is designed to:See how quickly you build a mental model of an unfamiliar systemUnderstand how you reason about signal, feedback, and failure modesObserve how deeply you engage with input quality as a leverLearn whether you enjoy the work itself, not just the outcomeCorrectness matters less than depth, curiosity, and systems intuition.The core messageWe are offering a path for people who love signal, precision, and deep work to apply that obsession to frontier AI.This role is not about having the right background. It is about having the right brain, the right stamina, and the desire to become excellent at something that does not quite have a name yet.

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About xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.About the Role As an AI Tutor - Economics, you will be instrumental in enhancing the capabilities of our cutting-edge technologies by providing high-quality input and labels using specialized software. Your role involves collaborating closely with our technical team to support the training of new AI tasks, ensuring the implementation of innovative initiatives. You'll contribute to refining annotation tools and selecting complex problems from advanced economics domains, with a focus on macroeconomic forecasting, microeconomic incentives, and behavioral experiments. This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. AI Tutor’s Role in Advancing xAI’s Mission As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. AI Tutors teach our AI models about how people interact and react, as well as how people approach issues and discussions in economics. To accomplish this, AI Tutors will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions. We seek individuals who are comfortable and eager to engage in these activities as a fundamental part of the role, ensuring a strong alignment with xAI’s goals and objectives to innovate. Scope An AI Tutor will provide services that include labeling and annotating data in text, voice, and video formats to support AI model training. At times, this may involve recording audio or video sessions, and tutors are expected to be comfortable with these tasks as they are fundamental to the role. Such data is a job requirement to advance xAI’s mission, and AI Tutors acknowledge that all work is done for hire and owned by xAI. Responsibilities Use proprietary software applications to provide input/labels on defined projects. Support and ensure the delivery of high-quality curated data. Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. Interact with the technical staff to help improve the design of efficient annotation tools. Choose problems from economics fields that align with your expertise, focusing on areas like macroeconomics, microeconomics, and behavioral economics.  Regularly interpret, analyze, and execute tasks based on given instructions. Key Qualifications Must possess a PhD in Economics or related field Proficiency in reading and writing, both in informal and professional English. Outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material. Strong passion for and commitment to technological advancements and innovation in economics. Preferred Qualifications Possesses experience with at least one publication in a reputable economics journal or outlet. Teaching experience as a professor. Location & Other Expectations This position is based in Palo Alto, CA, or fully remote. The Palo Alto option is an in-office role requiring 5 days per week; remote positions require strong self-motivation. If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time. We are unable to provide visa sponsorship. Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter. For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. Compensation $45/hour - $100/hour The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location. Benefits: Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

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About the role We’re hiring an AI Architect to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with ML teams in high-stakes meetings, scope and pitch solutions to top AI labs, and translate research needs (post-training, evals, alignment) into clear product roadmaps and measurable outcomes. You’ll drive end-to-end delivery—partnering with AI research teams and core customers to scope, pilot, and iterate on frontier model improvements—while coordinating with engineering, ops, and finance to translate cutting-edge research into deployable, high-impact solutions. What you’ll do Translate research → product: work with client side researchers on post-training, evals, safety/alignment and build the primitives, data, and tooling they need. Partner deeply with core customers and frontier labs: work hands-on with leading AI teams and frontier research labs to tackle hard, open-ended technical problems related to frontier model improvement, performance, and deployment. Shape and propose model improvement work: translate customer and research objectives into clear, technically rigorous proposals—scoping post-training, evaluation, and safety work into well-defined statements of work and execution plans. Translate research into production impact: collaborate with customer-side researchers on post-training, evaluations, and alignment, and help design the data, primitives, and tooling required to improve frontier models in practice. Own the end-to-end lifecycle: lead discovery, write crisp PRDs and technical specs, prioritize trade-offs, run experiments, ship initial solutions, and scale successful pilots into durable, repeatable offerings. Lead complex, high-stakes engagements: independently run technical working sessions with senior customer stakeholders; define success metrics; surface risks early; and drive programs to measurable outcomes. Partner across Scale: collaborate closely with research (agents, browser/SWE agents), platform, operations, security, and finance to deliver reliable, production-grade results for demanding customers. Build evaluation rigor at the frontier: design and stand up robust evaluation frameworks (e.g., RLVR, benchmarks), close the loop with data quality and feedback, and share learnings that elevate technical execution across accounts. You have Deep technical background in applied AI/ML: 5–10+ years in research, engineering, solutions engineering, or technical product roles working on LLMs or multimodal systems, ideally in high-stakes, customer-facing environments. Hands-on experience with model improvement workflows: demonstrated experience with post-training techniques, evaluation design, benchmarking, and model quality iteration. Ability to work on hard, ambiguous technical problems: proven track record of partnering directly with advanced customers or research teams to scope, reason through, and execute on deep technical challenges involving frontier models. Strong technical fluency: you can read papers, interrogate metrics, write or review complex Python/SQL for analysis, and reason about model-data trade-offs. Executive presence with world-class researchers and enterprise leaders; excellent writing and storytelling. Bias to action: you ship, learn, and iterate. How you’ll work Customer-obsessed: start from real research needs; prototype quickly; validate with data. Cross-functional by default: align research, engineering, ops, and GTM on a single plan; communicate clearly up and down. Field-forward: expect regular customer time and research leads; light travel as needed. What success looks like Clear wins with top labs: pilots that convert to scaled programs with strong eval signals. Reusable alignment & eval building blocks that shorten time-to-value across accounts. Crisp internal docs (PRDs, experiment readouts, exec updates) that drive decisions quickly. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$201,600—$241,920 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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ABOUT POOLSIDEIn this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. 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, engineering, infrastructure and deployment at scale. 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. They will create powerful economic engines. They will obsess over the success of their users and customers. poolside exists to be this company - to build a world where AI will be the engine behind economically valuable work and scientific progress.View GDPR PolicyABOUT OUR TEAMYou’ll join a tight-knit group of engineers and researchers from leading labs and product companies (DeepMind, Palantir, GitHub, among others). The culture is low-ego and high-bar, organized around hard problems. It’s a place to learn by building - side-by-side with people who care about craft, rigor, and impact - on challenges that matter and aren’t found anywhere else. Very few companies get a seat at this table, and all the ingredients are in place to give us the right to win. Now we just need to execute.ABOUT THE ROLEAs an FDRE, you'll be embedded with customers, figuring out how to build real agentic systems to solve hard problems.Hard problems aren’t solved from an armchair; the right to solve them comes from experience, resilience, and a little scar tissue, earned by engaging with reality.This role gives you direct exposure to frontier AI R&D and a front-row seat to the most valuable problems and industries on the planet. You’ll operate at the intersection of software engineering, applied AI and agent research, and product - designing and deploying high-reliability systems, while feeding signal back into our products and models.RESPONSIBILITIESFDREs work in small teams with the agility and autonomy of a startup, but with the experience and support of an established organization. Among other things, you willOwn the mission end-to-end. Be the technical owner in the field, clarify goals, shape the plan, make the hard calls, and ship systems that move real metrics.Partner for impact. Work directly with operators and executives to scope what matters most, then turn it into production results.Build with research in the loop. Collaborate with AI R&D on prompts, tools, and model improvements; bring back field-signals that make the next model, and the platform, better.Turn wins into a flywheel. Convert patterns into playbooks, products, and libraries so that every deployment is faster, more powerful, and more reliable than the last.WHAT YOU'LL SEE IN THE FIELDThese are the kinds of skills and technologies you’ll likely use and develop over time. Strong experience in any is a plus, not a prerequisite. We look for spikes!Software engineering & platforms: Backend services at scale; distributed systems; data/feature pipelines; queues/caching; fault tolerance.Agentic/LLM systems: multi-agent systems; agent communication/delegation; evals; long-running, fault-tolerant agents; tools/prompt/program design; guardrails.Evaluation & experimentation: Designing evals; monitoring performance/drift; fundamentals of Data Science/ML; able to turn a hazy problem into a structured exploration.Cloud & ops: Kubernetes, Docker, IaC (Terraform/CDK), networking, secrets, observability (Grafana/Prometheus/Datadog), CI/CD.Model ops: Fine-tuning/RL; designing agent environments; managing inference.Enterprise delivery: Security/compliance, data governance, integration with legacy systems.SKILLS & EXPERIENCEExceptional, high-agency, low-ego. You bias to action, collaborate well, and are motivated by impact and outcome.Learning-driven. You pick up new domains quickly, ask sharp questions, and turn are comfortable with ambiguity.Product-minded. You translate field pain into clean abstractions, docs, and tools others can use.Adventurer. You are eager and willing to travel and experience new things, and meet unforeseen challenges with creativity and resourcefulness.Excellent communicator. You express ideas clearly, listen actively, and build east rapport with customers and teammates alike.If you’re unsure whether you check every box, you should still apply! Impact beats pedigree here.PROCESSIntro call with a member of the Forward Deployed teamTechnical Interview with a Member of EngineeringInterview with (another) member of the Forward Deployed teamPeople Interview with Beatriz, Head of PeopleBENEFITSFully remote work & flexible hours;37 days/year of vacation & holidays;Health insurance allowance for you and dependents;Company-provided equipment;Wellbeing, always-be-learning and home office allowances;Frequent team get togethers in Paris;Great diverse & inclusive people-first culture.

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About the role We’re hiring an AI Architect to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with ML teams in high-stakes meetings, scope and pitch solutions to top AI labs, and translate research needs (post-training, evals, alignment) into clear product roadmaps and measurable outcomes. You’ll drive end-to-end delivery—partnering with AI research teams and core customers to scope, pilot, and iterate on frontier model improvements—while coordinating with engineering, ops, and finance to translate cutting-edge research into deployable, high-impact solutions. What you’ll do Translate research → product: work with client side researchers on post-training, evals, safety/alignment and build the primitives, data, and tooling they need. Partner deeply with core customers and frontier labs: work hands-on with leading AI teams and frontier research labs to tackle hard, open-ended technical problems related to frontier model improvement, performance, and deployment. Shape and propose model improvement work: translate customer and research objectives into clear, technically rigorous proposals—scoping post-training, evaluation, and safety work into well-defined statements of work and execution plans. Translate research into production impact: collaborate with customer-side researchers on post-training, evaluations, and alignment, and help design the data, primitives, and tooling required to improve frontier models in practice. Own the end-to-end lifecycle: lead discovery, write crisp PRDs and technical specs, prioritize trade-offs, run experiments, ship initial solutions, and scale successful pilots into durable, repeatable offerings. Lead complex, high-stakes engagements: independently run technical working sessions with senior customer stakeholders; define success metrics; surface risks early; and drive programs to measurable outcomes. Partner across Scale: collaborate closely with research (agents, browser/SWE agents), platform, operations, security, and finance to deliver reliable, production-grade results for demanding customers. Build evaluation rigor at the frontier: design and stand up robust evaluation frameworks (e.g., RLVR, benchmarks), close the loop with data quality and feedback, and share learnings that elevate technical execution across accounts. You have Deep technical background in applied AI/ML: 5–10+ years in research, engineering, solutions engineering, or technical product roles working on LLMs or multimodal systems, ideally in high-stakes, customer-facing environments. Hands-on experience with model improvement workflows: demonstrated experience with post-training techniques, evaluation design, benchmarking, and model quality iteration. Ability to work on hard, ambiguous technical problems: proven track record of partnering directly with advanced customers or research teams to scope, reason through, and execute on deep technical challenges involving frontier models. Strong technical fluency: you can read papers, interrogate metrics, write or review complex Python/SQL for analysis, and reason about model-data trade-offs. Executive presence with world-class researchers and enterprise leaders; excellent writing and storytelling. Bias to action: you ship, learn, and iterate. How you’ll work Customer-obsessed: start from real research needs; prototype quickly; validate with data. Cross-functional by default: align research, engineering, ops, and GTM on a single plan; communicate clearly up and down. Field-forward: expect regular customer time and research leads; light travel as needed. What success looks like Clear wins with top labs: pilots that convert to scaled programs with strong eval signals. Reusable alignment & eval building blocks that shorten time-to-value across accounts. Crisp internal docs (PRDs, experiment readouts, exec updates) that drive decisions quickly. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$201,600—$241,920 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With nine offices and facilities across the U.S., Europe, the Middle East, and the Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description:The Chief Engineer at Shield AI is responsible for solving complex technical challenges in deploying advanced autonomy solutions on Unmanned Aircraft Systems (UAS). As the chief authority on system architecture, design, development, risk mitigation, and product quality the Chief Engineer ensures the successful integration of Hivemind Autonomy across a range of aircraft, from small UAS to large autonomous collaborative platforms. This role is part of the Hivemind Solutions organization and leads a team of engineers to deliver cutting-edge autonomous capabilities for business-to-business and defense contracts. The ideal candidate has defense industry experience as a Chief Engineer and a proven track record of leading technical teams to develop and deploy autonomous systems.What you'll do:Serve as the Chief Engineer on Shield AI projects focused on developing and deploying autonomy solutions for unmanned aircraftLead a team responsible for advancing Hivemind Autonomy and shaping Department of Defense (DoD) autonomy architectures.Define and assign technical objectives, make key engineering decisions, and ensure the quality and completeness of all technical deliverablesProvide technical leadership and oversight across both Internal Research and Development (IRAD) initiatives and DoD contracts.Required qualifications:BS/MS in Computer Science, Electrical Engineering, Mechanical/Aerospace Engineering, and/or similar degree10+ years of industry experience in autonomy and/or UAS platforms (e.g., defense tech, self-driving car, etc.)7+ years of delivering software into production/certifiable environments with high-reliabilityUnderstanding of guidance, control and navigation (GNC) (e.g. controls, estimation, planning)Understanding of robotics stack (e.g., controls, estimation, perception, planning, etc.)Understanding of software development processes and how to effectively deploy softwareExperience defining technical scope and managing technical requirements, product architectures, ICDs and other system level design documentationDemonstrate problem solving skills by applying a scientific technical approachCustomer-facing engineering leader supporting both defense and internally funded development programsContribute to government contract proposal writingExcellent communication skills, both written and verbalExcellent leadership skills, driving a team of 6-20 engineers 176,620 - 264,930 a year#LI-LD2#LF Our international team members are employed through our Employer of Record (EOR) and receive a comprehensive international benefits package on top of base salary. For full details on compensation and benefits, please consult your talent acquisition partner.

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About the role We’re hiring an AI Architect to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with ML teams in high-stakes meetings, scope and pitch solutions to top AI labs, and translate research needs (post-training, evals, alignment) into clear product roadmaps and measurable outcomes. You’ll drive end-to-end delivery—partnering with AI research teams and core customers to scope, pilot, and iterate on frontier model improvements—while coordinating with engineering, ops, and finance to translate cutting-edge research into deployable, high-impact solutions. What you’ll do Translate research → product: work with client side researchers on post-training, evals, safety/alignment and build the primitives, data, and tooling they need. Partner deeply with core customers and frontier labs: work hands-on with leading AI teams and frontier research labs to tackle hard, open-ended technical problems related to frontier model improvement, performance, and deployment. Shape and propose model improvement work: translate customer and research objectives into clear, technically rigorous proposals—scoping post-training, evaluation, and safety work into well-defined statements of work and execution plans. Translate research into production impact: collaborate with customer-side researchers on post-training, evaluations, and alignment, and help design the data, primitives, and tooling required to improve frontier models in practice. Own the end-to-end lifecycle: lead discovery, write crisp PRDs and technical specs, prioritize trade-offs, run experiments, ship initial solutions, and scale successful pilots into durable, repeatable offerings. Lead complex, high-stakes engagements: independently run technical working sessions with senior customer stakeholders; define success metrics; surface risks early; and drive programs to measurable outcomes. Partner across Scale: collaborate closely with research (agents, browser/SWE agents), platform, operations, security, and finance to deliver reliable, production-grade results for demanding customers. Build evaluation rigor at the frontier: design and stand up robust evaluation frameworks (e.g., RLVR, benchmarks), close the loop with data quality and feedback, and share learnings that elevate technical execution across accounts. You have Deep technical background in applied AI/ML: 5–10+ years in research, engineering, solutions engineering, or technical product roles working on LLMs or multimodal systems, ideally in high-stakes, customer-facing environments. Hands-on experience with model improvement workflows: demonstrated experience with post-training techniques, evaluation design, benchmarking, and model quality iteration. Ability to work on hard, ambiguous technical problems: proven track record of partnering directly with advanced customers or research teams to scope, reason through, and execute on deep technical challenges involving frontier models. Strong technical fluency: you can read papers, interrogate metrics, write or review complex Python/SQL for analysis, and reason about model-data trade-offs. Executive presence with world-class researchers and enterprise leaders; excellent writing and storytelling. Bias to action: you ship, learn, and iterate. How you’ll work Customer-obsessed: start from real research needs; prototype quickly; validate with data. Cross-functional by default: align research, engineering, ops, and GTM on a single plan; communicate clearly up and down. Field-forward: expect regular customer time and research leads; light travel as needed. What success looks like Clear wins with top labs: pilots that convert to scaled programs with strong eval signals. Reusable alignment & eval building blocks that shorten time-to-value across accounts. Crisp internal docs (PRDs, experiment readouts, exec updates) that drive decisions quickly. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$201,600—$241,920 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Dataiku is The Universal AI Platform™, giving organizations control over their AI talent, processes, and technologies to unleash the creation of analytics, models, and agents. Providing no-, low-, and full-code capabilities, Dataiku meets teams where they are today, allowing them to begin building with AI using their existing skills and knowledge.Dataiku’s promise to our customers is to provide them with the software and support needed to accelerate their Data Science and Machine Learning maturity. Dataiku’s Data Science team is responsible for delivering on that promise. As an AI Deployment Strategist / Data Scientist at Dataiku, you will have the opportunity to participate in our customers' journeys, from supporting their discovery of the platform to coaching users and co-developing data science applications from design to deployment. You will primarily work with our customers in the financial services and insurance industries. You will gain hands-on experience coding in multiple languages (primarily Python, occasionally R, SQL, PySpark, JavaScript, etc.) and applying the latest big data technologies to real-world business use cases. Our ideal candidate is comfortable learning new languages, technologies, and modelling techniques while being able to explain their work to other data scientists and clients.  Key Areas of Responsibility (What You’ll Do) Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help our customers achieve success. Scope and co-develop production-level data science projects with our customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth. Experience (What We’re Looking For) French and English - fluent Curiosity and a desire to learn new technical skills. Empathy and an eagerness to share your knowledge with your colleagues, Dataiku’s customers, and the general public. Ability to clearly explain complex topics to technical as well as non-technical audiences. Over 5 years of experience with coding (Python, R, SQL). Over 5 years of experience building ML models.   Understanding of underlying data systems and platform mechanics, such as Cloud architectures, K8S, Spark, and SQL.  Bonus points for any of these Experience with Consulting and/or Customer-facing Data Science roles. Experience in the manufacturing industry. Experience with Spark, SAS, Data Engineering or MLOps. Experience developing web apps in JavaScript, RShiny, or Dash. Experience building APIs. Experience using enterprise data science tools. Passion for teaching or public speaking. #LI-Hybrid  What are you waiting for! At Dataiku, you'll be part of a journey to shape the ever-evolving world of AI. We're not just building a product; we're crafting the future of AI. If you're ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can't wait to welcome you to Dataiku! And if you’d like to learn even more about working here, you can visit our Dataiku LinkedIn page.   Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us at: reasonable-accommodations@dataiku.com     Protect yourself from fraudulent recruitment activity Dataiku will never ask you for payment of any type during the interview or hiring process. Other than our video-conference application, Zoom, we will also never ask you to make purchases or download third-party applications during the process. If you experience something out of the ordinary or suspect fraudulent activity, please review our page on identifying and reporting fraudulent activity here.

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Company OverviewResolveGrid is a recently funded startup building a next-generation SaaS platform focused on solving complex, real-world problems using modern software and AI. We are assembling a small, highly talented AI-first engineering team where engineers have meaningful ownership and influence from day one. Role OverviewWe are seeking a Founding Senior Full Stack Software Engineer with 10+ years of professional experience to help design, build, and scale ResolveGrid’s core SaaS platform. This is a hands-on role for someone who thrives in early-stage environments, takes end-to-end ownership, and actively uses AI as a core part of their development workflow. You will work across the entire stack—backend, frontend, and AI-powered capabilities—while helping define the technical direction and engineering culture of the company. Candidates must be based in Orange County, CA or willing to relocate and commute regularly to Irvine.ResponsibilitiesAct as a founding engineer, shaping architecture, engineering standards, and best practices.Design, build, and maintain end-to-end features across the ResolveGrid SaaS platform.Develop and operate backend services using Node.js with TypeScript/JavaScript.Build and evolve frontend application flows using modern JavaScript/TypeScript frameworks.Write and maintain Python services and supporting tools.Design and implement AI-powered features, including: Chat agents and autonomous agents, Context management and memory strategies, Prompt engineering, evaluation, and iteration, and Agent workflows and orchestration.Use AI coding agents (e.g., Cursor, Windsurf, Claude) as a first-class part of daily development.Make architectural decisions with scalability, reliability, and maintainability in mind.Collaborate closely with product and leadership on roadmap and execution.Debug production issues and continuously improve system performance and reliability.Mentor and help grow the engineering team over time. Required Qualifications7+ years of professional software engineering experience.Strong expertise in TypeScript/JavaScript and Node.js. Proven experience building and operating SaaS platforms.Solid production experience with Python.Hands-on experience building AI-driven systems, including LLM-based chat or agent workflows.Practical knowledge of prompt engineering, context/window management, and agent design patterns.Demonstrated experience using AI coding agents (e.g., Cursor, Windsurf, Claude).Experience deploying and operating systems on AWS, GCP, or Azure.Strong understanding of system design, APIs, and distributed systems.Comfortable operating with ambiguity and high ownership in an early-stage startup.Ability to work regularly from Irvine, CA (Orange County). Nice to HaveExperience scaling early-stage or recently funded products.Familiarity with vector databases, embeddings, and RAG architectures.Experience with security, authentication, and multi-tenant SaaS systems.Prior founding or early startup experience. Why Join ResolveGridBe a founding engineer with real ownership and influence.Join an AI-first, high-caliber engineering team that treats AI as a force multiplier.Build production-grade AI systems with real customer impact.Competitive compensation including meaningful equity.Opportunity to grow into technical leadership as the company scales.#LI-DNI #LI-Remote

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About xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.About the Role As an AI Tutor - Economics, you will be instrumental in enhancing the capabilities of our cutting-edge technologies by providing high-quality input and labels using specialized software. Your role involves collaborating closely with our technical team to support the training of new AI tasks, ensuring the implementation of innovative initiatives. You'll contribute to refining annotation tools and selecting complex problems from advanced economics domains, with a focus on macroeconomic forecasting, microeconomic incentives, and behavioral experiments. This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. AI Tutor’s Role in Advancing xAI’s Mission As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. AI Tutors teach our AI models about how people interact and react, as well as how people approach issues and discussions in economics. To accomplish this, AI Tutors will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions. We seek individuals who are comfortable and eager to engage in these activities as a fundamental part of the role, ensuring a strong alignment with xAI’s goals and objectives to innovate. Scope An AI Tutor will provide services that include labeling and annotating data in text, voice, and video formats to support AI model training. At times, this may involve recording audio or video sessions, and tutors are expected to be comfortable with these tasks as they are fundamental to the role. Such data is a job requirement to advance xAI’s mission, and AI Tutors acknowledge that all work is done for hire and owned by xAI. Responsibilities Use proprietary software applications to provide input/labels on defined projects. Support and ensure the delivery of high-quality curated data. Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. Interact with the technical staff to help improve the design of efficient annotation tools. Choose problems from economics fields that align with your expertise, focusing on areas like macroeconomics, microeconomics, and behavioral economics.  Regularly interpret, analyze, and execute tasks based on given instructions. Key Qualifications Must possess a PhD in Economics or related field Proficiency in reading and writing, both in informal and professional English. Outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material. Strong passion for and commitment to technological advancements and innovation in economics. Preferred Qualifications Possesses experience with at least one publication in a reputable economics journal or outlet. Teaching experience as a professor. Location & Other Expectations This position is based in Palo Alto, CA, or fully remote. The Palo Alto option is an in-office role requiring 5 days per week; remote positions require strong self-motivation. If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time. We are unable to provide visa sponsorship. Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter. For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. Compensation $45/hour - $100/hour The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location. Benefits: Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

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About Anyscale: At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the roleRay aims to provide a universal API for building distributed applications. To achieve this goal requires a distributed system with high levels of performance and reliability. We're looking for engineers with systems software experience that are interested in contributing to the Ray backend. About the Ray Core TeamThe Ray Core team develops and maintains the Ray C++ backend (e.g., distributed scheduler, language runtime integration, I/O and memory subsystems). We are responsible for the reliability, scalability, and performance of Ray as well as ensuring that Ray provides the right feature set to support higher level libraries and use cases. The team works on a balance of new features / distributed libraries, test infra improvements, debugging, and longer-term architectural improvements to Ray.A snapshot of projects you can work on:- Optimizing performance of large-scale workloads on Ray- Stability and stress testing infrastructure- Improving fault tolerance (HA)As part of this role, you will:Develop high quality open source software to simplify distributed programming (Ray)Identify, implement, and evaluate architectural improvements to Ray coreImprove the testing process for Ray to make releases as smooth as possibleCommunicate your work to a broader audience through talks, tutorials, and blog postsWe'd love to hear from you if you have:At least 2 year of relevant work experienceSolid background in algorithms, data structures, system designExperience in building scalable and fault-tolerant distributed systemsKnowledge of distributed model training and inference (e.g. tensor parallel, pipeline parallel) is preferredKnowledge of GPU programming is preferredAnyscale Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law.  Anyscale Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish