ashby
$130,000–$500,000 / year
Posted 2 days ago
Salary: $220,000–$600,000 / year
Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
Deeptune is an RL environments lab within Mercor that builds training gyms for AI agents: high-fidelity simulations where AI learns to perform real-world tasks through reinforcement learning. We work with the leading AI labs to help them train the next generation of agentic models, and our environments have already contributed to recent breakthroughs in computer use, code generation, and multi-step task completion. About You
You’re a strong engineer across backend and infrastructure (Python, Go, TypeScript, etc.) with a deep interest in agentic AI.
You'll also build direct partnerships with leading AI labs and enterprises, and contribute hands-on to improving frontier model quality through data, evaluation, and systems — work that sits squarely in the areas the field agrees matter most right now: RL with verifiable rewards, rubric-based reward modeling for subjective and agentic domains, and the pipelines that turn raw human demonstrations into training-ready environments.
This role requires high ownership and abstraction: setting direction, driving outcomes, and staying hands-on while leading.