---
title: 'Research Intern at Mercor'
canonical: 'https://feeny.ai/job/research-intern-mercor-san-francisco-3pgbj0ap6ca9'
type: 'job'
last_seen: '2026-10-17'
---

# Research Intern at Mercor

- **Company:** Mercor
- **Location:** San Francisco, CA
- **Employment:** internship
- **Work type:** onsite
- **Posted:** 2026-10-05
- **Last confirmed live:** 2026-10-17
- **Apply:** https://jobs.ashbyhq.com/mercor/e6502490-37c6-471a-9ffb-cf397764c518

## Job 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 Intern at Mercor, you’ll work on research at the frontier of post-training, reinforcement learning with verifiable rewards (RLVR), data generation, and model evaluation. You’ll investigate how datasets, rewards, and training methods affect the capabilities and behavior of large language models. This may include designing controlled experiments, developing new evaluation methodologies, conducting systematic failure analysis, and testing approaches to improve tool use, agentic behavior, and real-world reasoning. You’ll work closely with research scientists, research engineers, and domain experts to turn open-ended questions into rigorous experiments. Your work will contribute to Mercor’s research agenda and may support external publications, benchmark releases, and the development of frontier AI systems.

## What You’ll Do

- Develop and investigate research questions related to post-training, RLVR, data quality, and model evaluation.
- Design and run controlled experiments to understand how datasets, rewards, and training strategies affect model performance.
- Study reward-shaping and post-training methods, including approaches such as GRPO and DAPO.
- Develop methods for measuring data quality, usability, and performance uplift on key benchmarks.
- Design and evaluate datasets, rubrics, evaluators, and scoring frameworks for complex model capabilities.
- Conduct systematic error analysis to identify model failure modes and opportunities for improvement.
- Analyze experimental results and communicate findings through clear reports, research artifacts, and presentations.
- Build the research tooling and data pipelines needed to conduct experiments at scale.
- Collaborate with research scientists, research engineers, applied AI teams, and domain experts producing training and evaluation data.
- Contribute to research publications, benchmark releases, and other public research outputs where appropriate.

## What We’re Looking For

- Currently pursuing a master’s or PhD in computer science, machine learning, statistics, mathematics, or another relevant field.
- Demonstrated ability to formulate research questions, design experiments, and draw sound conclusions from empirical results.
- Demonstrated experience in at least one of the following:
- Training, fine-tuning, or evaluating language models.
- Agentic AI system, RL environments
- Developing benchmarks, evaluation methodologies, or data-quality measures.
- At least one publication or open source project.
- Strong programming skills, particularly in Python, and the ability to write reliable research code.
- Familiarity with machine learning fundamentals, experimental design, and statistical analysis.
- Intellectual curiosity.
- Comfort operating in a fast-paced research environment with rapid iteration and a high degree of ownership.

## Nice to Have

- Previous research experience in language models, reinforcement learning, model evaluation, or post-training.
- Experience training, fine-tuning, or evaluating language models.
- Familiarity with RLVR techniques, reward modeling, or agentic AI systems.
- Experience developing benchmarks, evaluation methodologies, or data-quality measures.
- Research publications or submissions at competitive CS conferences such as ACL, NeurIPS, ICML, ICLR, or EMNLP.
- Research papers, technical reports, open-source projects, or other work samples demonstrating relevant skills.

## Why Mercor

Impact: Your work powers how AI labs train and deploy their models Learning: Get early exposure to frontier AI research and engineering Growth: Work with a high-velocity team where interns ship to production

## Benefits

- Mentorship from experienced researchers.
- Work on real, high-impact projects.
- $1.5K monthly stipend for meals
- $200 monthly laundry reimbursement
- $200 monthly personal wellness reimbursement
- Free Equinox membership
- Team events and offsites.
- Potential full-time return offer.

## About Mercor

## Company Overview
- **One-liner**: Mercor organizes human intelligence to power the AI economy by connecting domain experts with frontier AI labs and enterprises for model training, evaluation, and deployment.
- **Entity Type**: Private (Series C)
- **Headquarters**: San Francisco, California, USA (with offices in New York City and London)
- **Founded**: 2023
- **Founders**: Brendan Foody & Adarsh Hiremath (Co-founders & Co-CEOs)

## Core Business
- Primary industry: AI Data & Infrastructure, Human-in-the-Loop AI, Enterprise AI
- Target customers: Frontier AI labs (OpenAI, Anthropic, etc.), Fortune 500 enterprises deploying AI in production, and domain experts seeking high-value AI work
- Mission: Organizing human intelligence to power the AI economy — building the layer between human expertise and frontier models.

## Products & Services
- **Mercor Platform**: A global network of millions of domain experts across 300+ professional fields, paid over $3 million per day to train frontier AI models. Experts are found and vetted using dynamic, role-specific AI interviews.
- **APEX Benchmark**: A benchmark family that measures AI's real-world impact on professional work, setting a standard for whether AI can perform economically valuable work.
- **Mercor Enterprise**: Brings Mercor's expert network and evaluation infrastructure to Fortune 500 companies, deploying custom AI agents, staffing teams with vetted domain experts, and helping organizations encode their own knowledge into AI systems.

## Market Standing
- **Valuation**: $10 billion valuation (as of Series C)
- **Key Metric**: Total Funding — $350 million Series C (recently raised); company is profitable
- **Notable Investors/Partners**: Not explicitly named in provided sources, but the company works with leading AI labs and Fortune 500 enterprises
- **Growth Signals**: 
  - Named to Bloomberg's "2026 24 AI Startups to Watch"
  - Forbes AI 50 (2025)
  - Forbes Cloud 100 (2025)
  - LinkedIn Top Startup (2025)
  - Described as "the fastest-growing company in the world"
  - Tens of thousands of skilled professionals earning an average of more than $95/hour on the platform

## Competitive Advantages
- **Massive, vetted expert network**: Millions of domain experts across 300+ fields, found and vetted via AI-driven interviews — a hard-to-replicate moat.
- **Direct frontier model exposure**: Every team works directly with frontier models, training them and building around them — most companies haven't imagined this level of integration.
- **Profitability at scale**: Profitable at Series C with a $10B valuation, indicating strong unit economics.
- **End-to-end AI infrastructure**: From expert sourcing and vetting to model evaluation (APEX) to enterprise deployment — a vertically integrated stack.

## Strategic Focus
- **Scaling the expert network**: Continuing to onboard millions of domain experts globally to meet the insatiable demand for high-quality human training data.
- **Enterprise AI deployment**: Expanding Mercor Enterprise to help Fortune 500 companies encode organizational knowledge into AI systems and deploy custom agents.
- **Benchmarking AI's economic impact**: Growing the APEX benchmark as the standard for measuring whether AI can perform economically valuable work.
- **Preparing for AGI**: The company's founding thesis is about answering what role humans will play in the economy as AGI approaches.

## Why Work Here
- **Culture**: "Built for people who thrive in high-velocity environments." Values include Intensity, Simplicity, User Obsession, High Standards, Can-Do Attitude, and Time Travelers (thinking ahead).
- **Work model**: In-person collaboration from offices in San Francisco, New York City, and London. No remote option — the company believes in-person collaboration helps move faster and solve harder problems.
- **Engineering culture**: Direct exposure to frontier AI research, labs, and startups. Every team works with frontier models daily. Described as "the fastest-growing company in the world."
- **Compensation**: Generous equity grants, competitive salaries (ranges from $100K–$500K depending on role), and a "proximity bonus" (generous annual housing support).
- **Benefits**: 
  - Unlimited paid vacation and sick days
  - Free Equinox membership (premium fitness access)
  - Monthly wellness stipend and free mental health services
  - Monthly food stipend
  - 401k with employer match
  - Parental leave for both birthing and non-birthing parents
- **Team**: "A team of ambitious, diverse people who want to work on what matters most." Open roles across Engineering (31 roles), Operations (15 roles), Enterprise (5 roles), Finance (4 roles), and more.

## Sources
1. [mercor.com](https://www.mercor.com/)
2. [mercor.com/careers](https://www.mercor.com/careers/)
3. [mercor.com/mission](https://www.mercor.com/mission/)
4. [jobs.ashbyhq.com/mercor](https://jobs.ashbyhq.com/mercor)
5. [linkedin.com/company/mercor-ai](https://www.linkedin.com/company/mercor-ai)

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