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Mercor

Research Engineer, Environments

Posted 3 Days Ago
Be an Early Applicant
In-Office
San Francisco, CA, USA
180K-500K Annually
Mid level
In-Office
San Francisco, CA, USA
180K-500K Annually
Mid level
Build end-to-end RL environments and verifiers from enterprise data: ship workflow extraction and grading models, automate task-refinement pipelines, platformize sandbox app clones with real data, deliver data to customers, and scale environment production while preserving high fidelity.
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About Mercor

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.

About the Role

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.

What You'll Do
  • 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.

What We're Looking For
  • 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 Have
  • 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

Benefits
  • Semi-annual performance bonus structure

  • Generous equity grant vested over 4 years

  • Up to $15k Relocation bonus

  • $10K housing bonus (if you live within 0.5 miles of our office)

  • $1.5K monthly stipend for meals

  • Free Equinox membership

  • $200 monthly laundry reimbursement

  • $200 monthly personal wellness reimbursement

  • Health, Dental, Vision insurance

HQ

Mercor San Francisco, California, USA Office

San Francisco, California , United States, 94105

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