Mercor
Research Scientist - Environments, Data and Post-Training
San Francisco
Sponsorship not specifiedDetected 28 days ago
Machine LearningResearch
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About the role
- As a Research Scientist at Mercor, you will work at the intersection of research and engineering on frontier post-training.
- Working with researchers, engineers, domain experts, and customers, you will investigate how data, rewards, environments, and optimization methods shape model behavior.
- Your work will influence frontier models, Mercor's products, and the broader research community through releasing blogposts, technical reports, and papers.
Responsibilities
- Implement novel post-training methods that improve model reasoning, tool use, and agentic behavior.
- Develop new training recipes for frontier open models.
- Design and run experiments across datasets, reward functions, environments, and optimization strategies, including methods such as GRPO and DAPO.
- Investigate model capabilities and failure modes, then develop targeted training interventions.
- Create methods for measuring data quality, usability, and causal impact on model performance.
- Build scalable pipelines for data generation, filtering, augmentation, and selection.
- Develop rubrics, evaluators, benchmarks, and scoring systems that inform training decisions.
- Collaborate with researchers, applied AI teams, engineers, and domain experts producing training data.
- You will develop new training and evaluation methods, test them through rigorous experiments, and implement successful approaches at scale.
Requirements
- Ability to reason rigorously about model behavior, experimental results, and data quality.
- Knowledge of the current AI research landscape and important open problems.
Nice to have
- Experience on an industry post-training or frontier-model team.
- Main authorship of publications at top-tier conferences (NeurIPS, ICML, ACL).
- Experience with synthetic-data generation
- Familiarity with APIs, databases, and cloud infrastructure.
Compensation
- Bi-annual performance bonus structure
Benefits
- Bi-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
- $200 monthly laundry reimbursement
- $200 monthly personal wellness reimbursement
- Health, Dental, Vision insurance
- Build reinforcement learning with verifiable rewards (RLVR) and other post-training pipelines at scale.
- Demonstrated experience training and evaluating machine learning models.
- A strong research record in post-training, reinforcement learning, language-model evaluation, data-centric ML, or a closely related field.
Company info
- 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.
This listing is sourced directly from Mercor's careers page and normalized into a canonical job model.