Research Engineer, Real Environments

The role

You will work with large enterprises to capture data and transform it into high-fidelity RL environments for capability evaluations and training datasets. The goal is to automate the process of building evals for real work in the economy.

What you will 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, loading real data into sandboxes, building prompts from real workflows, and writing verifiers.
• Systematize the production of environments to scale throughput while maintaining high-quality worlds and verifiers.

Required qualifications

• Prior experience shipping environments – contributed to an OSS framework, built environments at previous companies, or worked on agentic evaluations.
• Strong full-stack engineering skills.
• Bias to action.
• Curiosity.
• Sweat the details that make a simulation indistinguishable from the real thing.
• Systems-level thinking skills.

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

About the company

Mercor builds infrastructure that enables frontier AI labs and enterprises to train, evaluate, and improve AI on real-world professional work. The company is profitable and recently raised a $750 million Series D at a $20 billion valuation.