Scale AI jobs

Product Manager, Gen AI New York, NY; San Francisco, CA Scale AI builds the data infrastructure that powers the world's most advanced AI. We are the trusted data partner behind frontier model makers and enterprise AI teams - providing the high-quality training data, evaluation frameworks, and human-feedback systems that make models smarter, safer, and more capable. Scale operates as a two-sided marketplace. On the demand side , our customers - leading AI labs and enterprises - need precisely labeled, expert-curated data to train and evaluate their models. On the supply side , we work with a global network of 500,000+ skilled contributors across 100+ countries who perform the complex annotation, evaluation, and data-generation tasks that fuel AI progress. Product Managers at Scale sit at the intersection of these two sides, shaping the systems, tooling, and experiences that make this marketplace work at unprecedented quality and scale. We are hiring Product Managers across multiple teams within our GenAI organization. These roles span both demand-side products (the tools and platforms our customers interact with) and supply-side products (the systems that power our contributor ecosystem). Each role offers the opportunity to work on high-impact, technically complex problems at the frontier of AI - with dedicated engineering, design, and data science teams. About the Role - Scale's GenAI platform is how the world's leading AI companies - from frontier model labs to Fortune 500 enterprises - create the training data that makes their models best-in-class. As a PM here, you are building the systems

Software Engineer, Enterprise London, UK At Scale AI, we're not just building AI tools-we're pioneering the next era of enterprise AI. As businesses race to harness the power of Generative AI, Scale is at the forefront, delivering cutting-edge solutions that transform workflows, automate complex processes, and drive unparalleled efficiency for the largest enterprises. Our Scale Generative AI Platform (SGP) provides foundational services and APIs, enabling businesses to seamlessly integrate AI into their operations at production scale. We're looking for a Backend Engineer to help bring large-scale GenAI systems to production. In this role, you'll build the core infrastructure that powers AI products for some of the world's largest enterprises-designing scalable APIs, distributed data systems, and robust deployment pipelines that enable production-grade reliability and performance. This is a rare opportunity to be at the center of the GenAI revolution, solving hard backend and infrastructure challenges that make AI truly work at enterprise scale. If you're excited about shaping how AI systems are deployed and scaled in the real world, we want to hear from you. At Scale, we don't just follow AI advancements - we lead them. Backed by deep expertise in data, infrastructure, and model deployment, we are uniquely positioned to solve the hardest problems in AI adoption. Join us in shaping the future of enterprise AI, where your work will directly impact how businesses operate, innovate, and grow in the age of GenAI. You Will: - Design, build, and scale backend systems that power enterprise GenAI products, focusing on

Technical Lead Manager, Physical AI San Francisco, CA Scale AI is the data engine for the entire AI industry. Our mission is to accelerate the development of AI applications by providing organizations with the high-quality data they need. The Physical AI team at Scale is focused on the next frontier: building general AI that can reason and act in the physical world. By leveraging Scale's massive data infrastructure, we are helping frontier labs build Foundation Models for Physical AI that will redefine the future of automation. Role Overview As the Technical Lead Manager (TLM) for the Physical AI team of Scale , you will bridge the gap between cutting-edge Machine Learning research and physical robot deployment. You will lead a high-performing team of Research Engineers while remaining a hands-on technical contributor (~60% of your time). Your primary focus will be the development and evaluation of Large-Scale Foundation Models (e.g VLAs, World models) that allow robots and AVs to generalize across diverse tasks, environments, and morphologies. Key Responsibilities Technical Leadership & Research - Model Scaling: Direct research into scaling laws for Physical AI, determining how to best utilize massive datasets for pre-training and fine-tuning generalist policies. - VLA and World model development: Develop novel methods for developing and evaluating models, including new Physical AI industry benchmarks - Hands-on Modeling: Actively write code to implement, train and test SOTA architectures. Conduct research on Physical AI data collection, cross-embodiment training, and policy fine-tuning. - Data Strategy: Collaborate with internal labeling teams to design

Distinguished Engineer San Francisco, CA; New York, NY Job Description: Distinguished Engineer, Enterprise AI About Scale AI Our mission is to develop reliable AI systems for the world's most important decisions. The Enterprise AI business delivers performant, reliable, and production-grade AI applications to enterprises across all industries by providing Generative AI expertise and infrastructure. The Role We're seeking a Distinguished Engineer - a hands-on technical leader operating at the VP level - to shape the vision and technical roadmap of our core AI/ML infrastructure that powers enterprise AI applications. Reporting directly to the SVP of Engineering, Enterprise AI, this individual will drive long-term technical direction for our Scale GenerativeAI Platform (SGP), influence architectural decisions across the company, and partner closely with engineering and product leaders to bring advanced AI capabilities to enterprise customers. You'll serve as a cross-organizational thought leader - setting standards for technical excellence, mentoring senior engineers, and ensuring our systems and models meet the demands of global-scale deployment. This is a rare opportunity to influence both foundational AI infrastructure and the enterprise AI applications built on top of it. Responsibilities - Define and drive the technical strategy for Scale's AI/ML infrastructure and SGP platform, balancing short and long-term investments. - Partner with senior engineering and product leadership to ensure scalable, secure, and performant enterprise AI systems. - Lead architecture and design reviews across multiple teams, ensuring technical consistency and innovation. - Serve as a trusted advisor and mentor to principal engineers and technical leads across the organization.

Research Scientist, AI Controls and Monitoring San Francisco, CA; New York, NY Scale Labs, Research Scientist - AI Controls and Monitoring As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might: - Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs; - Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected; - Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps;

Software Engineer (Backend), Enterprise Budapest, Hungary At Scale AI, we're not just building AI tools-we're pioneering the next era of enterprise AI. As businesses race to harness the power of Generative AI, Scale is at the forefront, delivering cutting-edge solutions that transform workflows, automate complex processes, and drive unparalleled efficiency for the largest enterprises. Our Scale Generative AI Platform (SGP) provides foundational services and APIs, enabling businesses to seamlessly integrate AI into their operations at production scale. We're looking for a Backend Engineer to help bring large-scale GenAI systems to production. In this role, you'll build the core infrastructure that powers AI products for some of the world's largest enterprises-designing scalable APIs, distributed data systems, and robust deployment pipelines that enable production-grade reliability and performance. This is a rare opportunity to be at the center of the GenAI revolution, solving hard backend and infrastructure challenges that make AI truly work at enterprise scale. If you're excited about shaping how AI systems are deployed and scaled in the real world, we want to hear from you. At Scale, we don't just follow AI advancements - we lead them. Backed by deep expertise in data, infrastructure, and model deployment, we are uniquely positioned to solve the hardest problems in AI adoption. Join us in shaping the future of enterprise AI, where your work will directly impact how businesses operate, innovate, and grow in the age of GenAI. You Will: - Design, build, and scale backend systems that power enterprise GenAI products, focusing

Product Marketing Lead, GenAI San Francisco, CA At Scale, we develop reliable AI systems for the world's most important decisions. Scale's product marketing team is responsible for developing and executing strategies that drive awareness and adoption for Scale's offering. We understand our customers' needs and challenges and ensure that their voices are reflected in product development and messaging. We then partner closely with product, engineering, research, sales, comms, and the broader marketing team to create a cohesive customer experience across all our channels. This role sits at the center of Scale's GenAI data products, which power the world's leading AI labs. As one of the largest providers of high-quality AI training data, we've built our reputation on speed, quality, frontier research, and a growing suite of multimodal data capabilities. The market is evolving fast, and we're looking for a marketer who can go on offense to sharpen our narrative and build a playbook that earns the trust of the AI community. The ideal candidate combines strategic thinking with hands-on execution. You will: - Own positioning and messaging for Scale's GenAI data products, articulating our differentiation on data quality, delivery speed, and multimodal breadth in a way that resonates with AI researchers and technical buyers. - Lead the content and social strategy for Scale Labs ' dedicated online presence, taking a research-native approach that earns attention and credibility from the AI community. - Build and maintain competitive intelligence and a sharp point of view on the data market, arming the team

Senior Frontier Agents Engineer San Francisco, CA; New York, NY About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment - Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements - Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) - Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows - Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development - Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation - Architect multi-agent systems that orchestrate between different models, tools, and data sources

Research Scientist, Agent Robustness San Francisco, CA; New York, NY Scale Labs, Research Scientist - Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: - Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; - Design and build harnesses to test AI agents' tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; - Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer

National Security Hackathon 2026 - General Interest San Francisco, CA; New York, NY; Washington, DC National Security Hackathon Attendees - Stay Connected with Scale AI This posting is for candidates who attended National Security Hackathon and connected with a member of the Scale AI team. It was great meeting you at the Hackathon! Whether we spoke at our booth or on the floor, we always enjoy connecting with people who are passionate about advancing AI and machine learning. At Scale AI, our mission is to develop reliable AI systems for the world's most important decisions. For the past ten years, Scale has been the leading AI data foundry, supporting some of the most exciting advancements in AI, including generative AI, defense applications, robotics, and autonomous systems. We're continuing to grow our team across a range of technical and mission-focused roles. If you're excited about the problems we're tackling, feel free to share your information here. A member of our team will reach out if there's a strong fit with one of our open opportunities. And even if the timing isn't right today, we'd love to stay connected. We look forward to continuing the conversation. In the meantime, you can learn more about our work at scale.com . 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 and may be inclusive of several career levels at Scale;

Staff Software Engineer, Full-Stack - Enterprise Gen AI New York, NY; San Francisco, CA Staff Software Engineer, Full-Stack - Enterprise Gen AI Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a frontend-focused full-stack engineer to help build AI-powered applications that redefine enterprise workflows and push the boundaries of interactive AI. This role is ideal for someone who thrives in a fast-paced environment, enjoys working on a diverse set of projects, and has a passion for crafting high-quality, intuitive user experiences. At Scale, you'll work on a mix of cutting-edge customer-facing AI applications and internal SaaS products. Our engineering team powers projects like TIME's Person of the Year AI experience ( see it in action ), where our AI technology helped shape one of the most iconic features in media. You'll also contribute to Scale's GenAI Platform ( SGP ), a powerful system that enables businesses to build and deploy AI agents at scale. Whether it's developing interactive AI assistants, enterprise-grade web applications, or refining our core SaaS platform, you'll play a crucial role in shaping how AI integrates into real-world applications. You Will: - Build and enhance user-facing AI applications for major enterprise customers, including high-profile media and Fortune 500 companies - Develop and refine features for Scale's GenAI Platform , empowering businesses to build, deploy, and manage AI-driven agents - Design, build, and optimize polished, high-performance UIs using Next.js, React, TypeScript, and Tailwind

Channel Manager Doha, Qatar As Channel Manager, you will own and grow Scale AI's partner and channel ecosystem in Qatar - identifying, developing, and managing relationships with the technology partners, system integrators, and resellers that extend our reach across the market. You will work closely with the Country Lead and the broader go-to-market team to build a partner network that accelerates Scale's mission in Qatar and delivers measurable impact for government and enterprise customers. This is a high-impact, high-ownership role at the heart of one of Scale's most strategically significant markets. You will be operating at the intersection of national AI ambition and enterprise transformation and the work you do will directly shape how Qatar's institutions and organisations adopt and benefit from AI. What you'll do - Build and manage Scale AI's channel partner ecosystem in Qatar - identifying, recruiting, and onboarding Global & Local system integrators, technology partners, and value-added resellers aligned with Scale's mission and market priorities. - Drive partner-sourced pipeline and revenue working with partners to identify opportunities, structure joint go-to-market motions, and accelerate deals across government and enterprise segments. - Develop and execute joint business plans with key partners setting clear objectives, aligning on priorities, and holding partners accountable to agreed outcomes. - Enable partners to effectively represent Scale AI's portfolio designing and delivering training, certification, and enablement programmes that build genuine product and solution fluency. - Serve as the primary relationship owner for Scale's channel partners in Qatar building deep, trusted relationships at the leadership

Machine Learning Research Scientist, Reasoning San Francisco, CA; Seattle, WA; New York, NY About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, fueling the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we're amplifying access to high-quality data to drive progress toward Artificial General Intelligence (AGI). Building on our history of model evaluation with enterprise and government customers, we are expanding our capabilities to set new standards for both public and private evaluations. About This Role This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). The ideal candidate will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale's data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning. Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning , collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions. Ideally, you'd have: - Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or

Frontier Agent Engineering Manager, Enterprise San Francisco, CA; New York, NY About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment - Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements - Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) - Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows - Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development - Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation - Architect

Senior Software Engineer, GenAI San Francisco, CA; New York, NY About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we're accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world's most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. Our Approach As part of the interview process, you'll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. Together, these teams power Scale's AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data

Machine Learning Research Scientist, Post-Training San Francisco, CA; Seattle, WA; New York, NY Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: - Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. - Design and experiment new approaches to preference optimization. - Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. - Publish research findings in top-tier AI conferences. Ideally you'd have: - Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. - Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. - Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. - Excellent written and verbal communication skills - Published research in areas of machine learning at major conferences (NeurIPS,

Forward Deployed Engineer, GenAI San Francisco, CA; New York, NY About Scale AI At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we're accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI) and building upon our prior model evaluation work with enterprise customers and governments to deepen our capabilities and offerings for public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world's most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce is some of the most critical work for how humanity will interact with AI. About Our FDE Team Generating high-quality data is the core problem our business solves. We aim to make producing and delivering high-quality data seamless and efficient for operators and customers. Our Team is building customer and operator-specific infrastructure to provide high-quality data with low turnaround time. You'll be exposed to the cutting edge of the Generative AI industry while directly interfacing with the leading model-building organizations in the space, including the top AI research labs and government agencies. Join us in shaping the future of Artificial General Intelligence. As a Forward Deployed Engineer, you'll be at the forefront of providing

Principal Research Scientist - AI Scaling & Optimization Mountain View, California; San Francisco, California Principal Research Scientist - AI Scaling & Optimization P-1227 About Databricks AI At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development, by building and running the world's best data and AI platform. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI is committed to the belief that a company's AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. About the Scaling Research Team The Databricks AI Scaling team focuses on pushing the boundaries of large language model (LLM) training and inference efficiency beyond what is required to support existing models. The team explores novel avenues for scaling and efficiency improvements across algorithms, systems, and infrastructure, requiring researchers who can both drive independent research agendas and dive deep into low‑level implementation details with engineering partners. Role Summary As a Principal Research Scientist - Scaling, you will lead a team of world‑class researchers and engineers to advance the state of the art in large‑scale machine learning, focusing on post-training, RL and inference efficiency, optimization, and scaling. You will define and execute a research roadmap that advances the Databricks AI platform and delivers tangible improvements to how customers train,

Machine Learning Systems Research Engineer, Agent Post-training - Enterprise GenAI San Francisco, CA; New York, NY AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research and resources that serve all of our enterprise clients. As an ML Sys Research Engineer, you'll work on building out the algorithms for our next-gen Agent RL training platform, support large scale training, and research and integrate state-of-the-art technologies to optimize our ML system. Your customer will be other MLREs and AAIs on the Enterprise AI team who are taking the training algorithms and applying them to client use-cases ranging from next-generation AI cybersecurity firewall LLMs to training foundation healthtech search models. If you are excited about shaping the future of the modern AI movement, we would love to hear from you! You will: - Build, profile and optimize our training and inference framework. - Post-train state of the art models, developed both internally and from the community, to

ML Research Engineer, ML Systems San Francisco, CA; Seattle, WA; New York, NY Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale's ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: - Build, profile and optimize our training and inference framework - Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation - Research and integrate state-of-the-art technologies to optimize our ML system Ideally you'd have: - Strong excitement about system optimization - Experience with multi-node LLM training and inference - Experience with developing large-scale distributed ML systems - Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. - Strong written and verbal communication skills and the ability to operate in

Senior Staff Frontier Agents Engineer San Francisco, CA; New York, NY About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment - Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements - Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) - Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows - Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development - Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation - Architect multi-agent systems that orchestrate between different models, tools, and

Senior/Staff Machine Learning Research Engineer, General Agents, Enterprise GenAI San Francisco, CA; New York, NY Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale's Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you'll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle-from model and system design to evaluation, deployment, and iteration-bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: - Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. - Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. - Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance,

Machine Learning Research Engineer, Agent Data Foundation - Enterprise GenAI San Francisco, CA; New York, NY AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research, tools, and resources that serve all of our enterprise clients. As MLRE on the Data Foundation team, you'll work on cutting edge research to define the data flywheel that makes the whole machine move. This includes research around synthetic environments from task definitions, building agents for trace analysis, and contributing to a cutting edge framework that automatically hill-climbs agent-building from an eval set. This will involve creating best-in-class Agents that achieve state of the art results through a combination of post-training + agent-building algorithms. If you are excited about shaping the future of the modern GenAI movement, we would love to hear from you! You will: - Build synthetic data pipelines to generate enterprise environments to use for RL post-training - Create agents to convert traces from production into

Senior / Staff Machine Learning Research Scientist, Agents San Francisco, CA; Seattle, WA; New York, NY About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we're accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale's Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to