Research Engineer, Environments

Mercor•San Francisco, CA

3d•$180,000 - $500,000•Onsite

About The Position

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. You’ll work with large enterprises to capture their data and transform it into high-fidelity RL environments for capability evaluations and training datasets for frontier labs. We focus on pushing the frontier of world-building, verifier engineering, and more alongside our partners. Your goal will be to automate the process of building evals for real work in the economy.

Requirements

Prior experience shipping environments – you’ve contributed to an OSS framework, built environments at previous companies, or worked on agentic evaluations.
Strong full-stack engineering skills – you’ll be responsible for everything from infrastructure to app code to analytics
Bias to action – this team is focused on shipping evals, not just philosophizing about them.
Curiosity – being biased towards understanding and digging deep into model behavior and actually looking at the data.
Sweat the details that make a simulation indistinguishable from the real thing and have systems-level thinking skills that allow you to scale up quality.

Nice To Haves

Experience with Temporal, Modal, or similar orchestration/compute services
Experience with synthetic data generation for frontier models.
Past work auditing and scrutinizing industry-standard evaluations

Responsibilities

Ship models for workflow extraction, classification, and grading.
Engineer autonomous task refinement processes which distill data taste into pipelines.
Deliver data to customers and deploy into real engagements.
Help define the future of agentic transformation for enterprises around the world.
Deeply learn about the intricacies of enterprises through building evaluations for all aspects of work.
Build end-to-end environments for labs & enterprises by platformizing sandbox app clones, load real data into the sandboxes, build prompts from real workflows, and write verifiers leveraging enterprise expertise & golden outputs.
Systematize the production of environments to scale throughput while maintaining high-quality worlds and verifiers.