Scale AI

Scale AI is hiring ML Research Engineers to bridge the gap between frontier research and real-world impact for global governments. The role involves leading research into Agent design, Deep Research, and AI Safety/reliability, developing novel methodologies for public sector applications and setting new standards across the organization. Responsibilities include pioneering novel architectures, leading AI safety initiatives, driving deep research capabilities, publishing, consulting, and building evaluation frontiers.

Scale AI is seeking a Technical Lead Manager for their Physical AI team to lead research engineers in developing and evaluating Large-Scale Foundation Models for robots and AVs. The role involves hands-on contributions to model scaling, VLA/world model development, and data strategy, alongside team mentorship and translating research into production-ready features.

Director of Forward Deployed Engineering at Scale AI, leading a team to deliver and integrate AI agents for large enterprise customers. The role involves owning end-to-end delivery, technical oversight of agents, models, evaluations, and infrastructure, and partnering with Product teams to translate field lessons into reusable platform capabilities. Requires strong leadership, hands-on AI stack fluency, and experience deploying AI in complex enterprise environments.

Scale AI is seeking a Staff Applied AI Engineer to build advanced AI agents for enterprise clients using their Generative Platform (SGP). The role involves owning and optimizing AI solutions, leveraging SGP for multimodal functionality and tool-calling, gathering business requirements, collaborating with clients, and pushing production code in customer and Scale codebases. The ideal candidate has 7+ years of experience, a strong engineering background, and familiarity with data-driven ML model iteration and cloud environments.

Director of Enterprise ML at Scale AI, leading research scientists and engineers in GenAI initiatives. The role involves defining and driving a multi-year research roadmap, collaborating cross-functionally, and communicating research outcomes. Focus is on turning research into production-ready systems, with experience in evaluation, post-training, agents, and RL environments. Requires strong research background, publications, and team leadership experience.

Research Scientist role focused on designing and building evaluation measures, harnesses, and datasets for frontier AI systems, with a focus on identifying and mitigating risks. The role involves collaboration with external agencies and publishing findings, bridging AI research and policy.

Research Scientist focused on agent robustness, AI safety, and risk evaluations. The role involves researching AI agent capabilities, designing tests for harmful actions, creating exploits and mitigations for failure modes, and characterizing risks in multi-agent systems. Experience with post-training techniques like RLHF and published research in generative AI is required.

Research Scientist role focused on designing methods, systems, and experiments for AI controls and monitoring, ensuring advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. This includes developing monitoring techniques, researching layered control mechanisms, designing red-team simulations, and collaborating with policymakers.

This role is for a Machine Learning Fellow focused on evaluating, interpreting, and optimizing advanced generative AI systems. The fellow will engage in ML projects, contribute to research publications, and collaborate with AI labs and platforms. The role requires a PhD or postdoctoral degree in a related field and experience with Python and ML frameworks.

Senior/Staff Machine Learning Engineer on the General Agents team, responsible for designing, building, and deploying production-ready AI agents for enterprise use cases. This role involves working across the full agent lifecycle, from model and system design to evaluation, deployment, and iteration, bridging cutting-edge agentic techniques with real-world deployment constraints.

This role is for an Engineering Manager on the Enterprise team at Scale AI, focusing on being a technical bridge between Scale AI's AI capabilities and strategic enterprise customers. Responsibilities include understanding customer challenges, leading a team to architect and deploy AI solutions (specifically AI agents and integrations), prompt engineering, and RAG systems. The role requires strong software engineering and management experience, Python expertise, and cloud platform familiarity, with a focus on customer-facing AI deployments.

Distinguished Engineer to shape the vision and technical roadmap of core AI/ML infrastructure powering enterprise AI applications, driving long-term technical direction for the Scale GenerativeAI Platform (SGP), influencing architecture, and partnering with leaders to deliver advanced AI capabilities to enterprise customers. This hands-on technical leader will set standards, mentor senior engineers, and ensure global-scale deployment readiness.

Manager for a GenAI research team focused on evaluation, post-training, agents, and RL environments. The role involves leading a team, defining research roadmaps, driving execution, and collaborating cross-functionally. Requires a strong research background with publications and experience in fast-paced environments.

Scale AI is seeking a Staff Machine Learning Research Scientist to lead the development of novel evaluation methodologies, metrics, and benchmarks for large language models (LLMs). This role focuses on defining and measuring the capabilities and limitations of frontier LLMs, driving research that informs internal roadmaps and the broader community. Responsibilities include researching existing evaluation techniques, designing new benchmarks, implementing scalable evaluation pipelines, publishing findings, and mentoring junior researchers. The ideal candidate has 5+ years of experience in LLMs/NLP, a strong publication record, and experience leading research teams.

Scale AI is seeking a Staff Machine Learning Research Engineer focused on post-training algorithms for complex agents in enterprise GenAI applications. The role involves building a next-generation Agent RL training platform, integrating cutting-edge research, and training state-of-the-art models for enterprise customers, including cybersecurity and healthtech use cases. Experience with LLM training, post-training methods like RLHF/RLVR, and publications in top conferences are required.

Scale AI is seeking an ML Systems Research Engineer to work on building algorithms for their next-gen Agent RL training platform, supporting large-scale training, and researching/integrating state-of-the-art technologies to optimize ML systems. The role involves post-training state-of-the-art models for enterprise engagements and creating next-gen agent training algorithms for multi-agent/multi-tool rollouts.

Research Engineer focused on building and training advanced AI agents for enterprise GenAI applications, utilizing post-training and agent-building algorithms on real-world datasets to achieve state-of-the-art results.

This role focuses on researching and building synthetic data pipelines and agents to improve enterprise GenAI models. It involves creating agents for trace analysis, contributing to an agent-building framework, and training state-of-the-art models using post-training and agent-building algorithms.

Engineering Manager for AgentOps team focused on building an Agent Development Platform to manage agent lifecycles, including building, deploying, monitoring, evaluating, and improving agents. The platform aims to support RL workflows and knowledge capture for continuous performance improvements.

Scale AI is looking for a Staff/Senior Staff ML Engineer to lead Deep Research Agent Development for enterprise applications. This role involves setting technical strategy, driving research to production, and leading a team in building, orchestrating, and evaluating multi-agent systems at scale. Requires strong experience in Generative AI, LLMs, and AI Agents, with a focus on integrating diverse data modalities and ensuring production-readiness.

Machine Learning Research Scientist focused on reasoning in LLMs, specifically for agentic systems like browser and software engineering agents. The role involves studying critical data types, identifying effective data sources and methodologies to improve LLM reasoning, and contributing to research while collaborating with engineering teams to implement solutions.

Senior Forward Deployed AI Engineer for Scale AI's Enterprise team, acting as a technical bridge to strategic customers. Responsibilities include understanding customer challenges, architecting custom AI solutions, ensuring successful deployment and adoption of AI systems, developing production-grade AI agents and multi-agent systems, implementing evaluation frameworks, prompt engineering, RAG, fine-tuning, and collaborating with customer and internal teams. Requires strong software engineering, Python, ML/AI frameworks, and cloud platform experience.

ML Research Engineer focused on building and optimizing the internal distributed framework for large language model training and inference, supporting ML research and development.

Research Scientist focused on LLM post-training techniques (SFT, RLHF, reward modeling) to enhance text and multimodal capabilities. Involves optimizing data curation, analyzing model behavior, and publishing findings.

Lead applied ML engineering on Scale's Applied ML team, focusing on building and deploying scalable multi-agent systems to validate agentic reasoning and behaviors, scale human expertise, and drive research into real-world agent reliability failures, shipping production fixes.

Research Scientist role focused on building state-of-the-art AI agents, studying essential data types for agents like browser and SWE agents, and guiding data strategy to advance intelligent, adaptable AI agents. The role involves contributing to research publications, collaborating with customer researchers, and translating advancements into scalable solutions.

Scale AI is seeking a Tech Lead/Manager for their LLM Evals Research team. This role involves leading a team to develop and implement novel evaluation methodologies, metrics, and benchmarks for large language models, focusing on areas like instruction following, factuality, robustness, and fairness. The position requires research into LLM evaluation techniques, communication with clients and internal teams, implementation of scalable evaluation pipelines, and publishing research findings. The ideal candidate has extensive experience in LLMs, NLP, and Transformer modeling, with a proven track record of research impact and team leadership.

Senior Machine Learning Engineer focused on deploying and improving generative AI, computer vision, reinforcement learning, and agentic AI models for mission-critical government systems. The role involves building agent frameworks, fine-tuning models, and advancing research in RL for LLMs, with a strong emphasis on production environments and large datasets.

This role focuses on evaluating and interpreting advanced generative AI systems, designing datasets for rigorous evaluation, and contributing to research publications. It involves collaborating with AI labs and platforms to enhance model accuracy and reasoning, positioning it as a key player in the AI evaluation gate.

This role is for a Software Engineer Fellow focused on evaluating and interpreting advanced generative AI systems within the Human Frontier Collective program. The fellow will design datasets, evaluate AI models, and contribute to research publications, aiming to enhance AI accuracy and reasoning.

This role focuses on evaluating advanced generative AI systems by designing domain-specific problems and datasets, providing expert insights to enhance model performance, and contributing to research publications. It's a research-oriented role within a fellowship program aimed at shaping the future of AI.

This role focuses on building and scaling the infrastructure for large-scale AI model training, specifically the 'Operating System' for GPU clusters. It involves architecting a high-performance training platform, managing multi-tenant orchestration, optimizing job scheduling, and ensuring deep observability and reliability for massive workloads. The goal is to maximize the efficiency and velocity of AI researchers training advanced models.

Staff Software Engineer at Scale AI focused on building core product building blocks for agentic capabilities in the public sector. Responsibilities include processing federal datasets for real-time decision-making, developing multi-layered guardrails around agents, optimizing data retrieval, orchestrating asynchronous agents, and alerting users to data deviations. The role involves mentoring engineers, defining technical strategy for agentic features, ensuring system reliability, and consulting on AI-powered solutions for federal contracts.

ML Systems Engineer focused on building and scaling serving platforms for robotics-related foundation models, optimizing algorithms for cloud GPUs, and developing internal platforms for model capability discovery. The role involves backend system design, ML infrastructure, and ensuring low latency for real-time applications.

This role is for a Machine Learning Fellow focused on designing, evaluating, and interpreting advanced generative AI systems. The fellow will work on ML projects, contribute to research publications, and engage with a community of AI researchers. The role involves optimizing PyTorch models, evaluating ML code, advising on GPU optimization, and collaborating on research papers.

This role involves applying academic and professional expertise to design, evaluate, and interpret advanced generative AI systems. The fellow will work on ML projects, optimize PyTorch models, evaluate ML code, advise on GPU optimization, and contribute to research publications and technical reports.

Product Manager for AI Applications in the Global Public Sector at Scale AI, focusing on developing custom AI solutions and LLMs for government clients. The role involves leading cross-functional teams, understanding client needs, and ensuring the successful delivery of AI-powered products.

Senior Forward Deployed Data Scientist/Engineer to partner with enterprise customers, understand workflows and pain points, and build end-to-end data products and AI/ML systems. This role involves defining metrics, designing experiments, building tools (evaluation explorers, workflow applications, decision-support systems), and driving solutions into production, with a focus on measurable business impact and rigorous evaluation. Experience with AI-assisted development tools is expected.

This role focuses on building and scaling automated evaluation pipelines for AI systems, including LLMs and agentic models, to ensure their reliability, safety, and effectiveness in mission-critical government environments. It involves designing test datasets, benchmarks, and frameworks for various metrics, including LLM-judge evaluations, agent testing, and stress tests.

This role focuses on evaluating and interpreting advanced generative AI systems by designing domain-specific problems and datasets, providing expert insights to enhance model performance, and contributing to research publications. It's a research-oriented fellowship with a focus on AI evaluation.

Product Manager for Agentic AI platforms supporting national security decisions, focusing on the entire lifecycle from design to launch, with a strong emphasis on government and regulated environments, ethical AI, and risk management.

Tech Lead Manager for MLRE, ML Systems at Scale AI, focusing on building and optimizing the internal distributed framework for large language model training and evaluation. The role involves collaborating with ML teams to accelerate research and development, and integrating state-of-the-art technologies to optimize the ML system, supporting both training and inference.

AI Product Manager to own the Agent & Reinforcement Learning Environments data vertical, focusing on Computer Using Agent (CUA) data. Responsibilities include owning the product roadmap, data generation pipelines, quality, and researcher-facing tools for training and evaluating intelligent agents. Requires a blend of entrepreneurial, go-to-market, and technical skills, with experience in product management and understanding of RL, simulation environments, and data pipelines for model training/evaluation.

Product Manager for AI Applications within Scale AI's Global Public Sector team, focusing on developing bespoke AI solutions for governments and government-backed entities. This role involves leading cross-functional teams to build custom AI applications and LLMs, leveraging the Scale GenAI Platform, and ensuring customer success through client workshops, use case scoping, and continuous feedback.

Seeking a Principal Architect to lead a team of 50+ engineers in designing, developing, and deploying agentic AI products, focusing on LLMs and AI agents, for defense applications. The role involves technical direction, executive stakeholder engagement, and strategic planning, with success metrics tied to customer demonstrations and contract awards.

Engineering Manager to lead a Forward Deployed Engineering (FDE) team focused on delivering high-impact GenAI solutions in production for enterprise customers. The role involves leading, mentoring, and growing the team, working hands-on with customers to solve complex business and technical challenges, and shaping the product roadmap based on customer needs.

This role focuses on evaluating and interpreting advanced generative AI systems by designing domain-specific problems and datasets, providing expert insights to enhance model performance, and contributing to research publications. It involves collaboration with AI labs and Scale's research team.

Scale AI is seeking an Applied AI Engineer for their Enterprise team in London, UK. The role involves working with clients to build advanced AI agents and ML solutions using the Scale Generative Platform (SGP), focusing on enterprise needs such as cybersecurity and genomics. Responsibilities include owning AI strategy, leveraging SGP for agent development (including multimodal and tool-calling features), gathering business requirements, collaborating with clients and internal teams, and deploying production code. The ideal candidate has a strong engineering background, Python proficiency, and experience with cloud ML development. Familiarity with Generative AI in production is a plus.

Senior AI Infrastructure Engineer focused on building and maintaining scalable, reliable, and efficient platforms for serving LLMs. The role involves backend system design, integrating models, developing monitoring solutions, and leading projects end-to-end. Requires strong programming skills and experience with LLM serving fundamentals and container orchestration.

Scale AI is seeking an Applied AI Engineer to build advanced AI agents for enterprise clients using their Generative Platform (SGP). The role involves owning AI solutions for complex technical problems, leveraging multimodal functionality and tool-calling, and collaborating with clients and internal teams. The engineer will push production code and work with data-driven experiments to improve product performance.