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Mercor

Research Scientist - Environments, Data and Post-Training

  • Office
  • 3-6 years

Salary

$250,000 - 500,000/ year

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Description

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

As a Research Scientist at Mercor, you will work at the intersection of research and engineering on frontier post-training. You will develop new training and evaluation methods, test them through rigorous experiments, and implement successful approaches at scale.

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.
  • Build reinforcement learning with verifiable rewards (RLVR) and other post-training pipelines at scale.
  • 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.
  • Translate open-ended research questions into rigorous experiments and production systems.
  • Collaborate with researchers, applied AI teams, engineers, and domain experts producing training data.
  • Contribute to open-source post-training tools and research.

Requirements

  • 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.
  • Ability to reason rigorously about model behavior, experimental results, and data quality.
  • Strong programming skills and experience implementing machine learning systems.
  • Knowledge of the current AI research landscape and important open problems.
  • Excitement to work in person in San Francisco, five days a week (with optional remote Saturdays), and thrive in a high-intensity, high-ownership environment.
  • 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
  • Experience building large-scale evaluation or data-generation infrastructure.
  • Solid foundations in distributed or backend systems, and experimental design.
  • Familiarity with APIs, databases, and cloud infrastructure.

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
  • Free Equinox membership
  • $200 monthly laundry reimbursement
  • $200 monthly personal wellness reimbursement
  • Health, Dental, Vision insurance

Where you’d work

From the office, 4 or more days a week in the office

The office

Relocation offered

About the company

Mercor

  • Industry: AI

Office in San Francisco, United States

Also hiring in New York City, United States and United States

Your chances

Worth a look before you spend an evening tailoring a CV for it.

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  • 4 red flags

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Details13 facts · Role, Location, Compensation, Employment, Company
Type
Full-time
Equity
Equity offered
Industry
AI
Specialty
Data Science
Region
United States
Pay period
Annual
Show 7 more factsShow less

Role

Category
Data & Analytics
Specialty
Data Science
Experience
4+ years

Location

Work model
Office
Region
United States
Office
  • San Francisco, United States
Days in the office
4 or more days
Relocation
Offered

Compensation

Salary
$250,000 - 500,000 / year
Pay period
Annual
Equity
Equity offered

Employment

Type
Full-time

Company

Industry
AI

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