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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

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.

1e:T1688,

About Mercor

About the Role

As a Data Science Intern at Mercor, you’ll join a fast-moving, metrics-driven engineering team whose work shapes decisions across the company. You’ll analyze data that directly affects ranking, hiring efficiency, candidate experience and revenue, work with production datasets from your first week, and ship insights that product and engineering act on.

You’ll start on the analyses and tooling your team has wanted but hasn’t had the hands for, and as needs come up you’ll take deep ownership of them, with a named mentor alongside you. You’ll move quickly while keeping a high bar for analytical rigor, clarity and statistical correctness.

Where You’ll Work

Interns start on a rolling basis, so summer, spring and fall terms all work. About three weeks before your start we’ll match you to one of two teams:

Product Data Science. The data science function for the marketplace and talent platform: metrics for matching, ranking and hiring efficiency, event instrumentation and data integrity, experiments on the candidate and customer experience, and scoring models that change who gets surfaced for which role.
Applied AI Data Science. The data science function inside the org that delivers human data and evaluations to frontier AI labs: operational analytics for live customer projects, automated quality control that gates what ships, and evaluation science that shows a lab where its model breaks and why.

What You’ll Work On

Defining north-star metrics and feature-level KPIs for ranking, interview analytics and payouts
Designing A/B tests and quasi-experiments and turning results into product decisions within days
Building dashboards and lightweight data models so teams can self-serve insights
Instrumenting events with engineers and improving data quality, observability and latency
Prototyping models, from baselines to gradient boosting, to improve matching and scoring
Evaluating LLM-powered systems through rubric design, human-in-the-loop experiments and guardrail testing

What We’re Looking For

Pursuing a degree in a quantitative field, graduating 2027 (potentially 2028)
Strong fundamentals in statistics, SQL and Python
Experience with experiment design, causal reasoning and data analysis
Clear communication with engineers, product managers and leadership
Curiosity about LLM evaluation, retrieval, ranking or marketplace dynamics
Excited to work in person in San Francisco
Nice to have: dbt, dashboarding tools, recommendation or search metrics, LLM and agent evaluation

Why Mercor

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

Compensation and Benefits

$10K housing bonus if you live within 0.5 miles of our office during your internship
$1.5K monthly stipend for meals/rideshare
Health, dental and vision insurance
401(k) eligibility

1f:T1224,

About Mercor

About the Role

As a Member of Technical Staff, Intern at Mercor, you’ll join a small, product-driven engineering team building the systems behind how the world’s leading AI labs source expert talent and human data. You’ll write production code from your first week and ship work that reaches customers.

You’ll start on the work your team has wanted to do but hasn’t had the hands for, and as needs come up you’ll take deep ownership of them, with a named mentor alongside you. You’ll work closely with product and design, move fast, and hold a high bar for quality, scalability and simplicity.

Where You’ll Work

Interns start on a rolling basis, so summer, spring and fall terms all work. About six weeks before your start we’ll match you to the team where you’ll have the most impact, across one of the engineering sub-departments:

Talent platform. The marketplace that sources, vets, matches and pays expert talent.
Applied AI. Delivery systems, quality control and evals for the human data we ship to frontier labs.
Agents. Internal agents that automate operational work across the company.
Platform engineering. Shared infrastructure, contracts, payments and reliability.
Studio. The platform for creating and analyzing datasets.

What We’re Looking For

Pursuing a degree in Computer Science or a related field, graduating 2027 to 2029
Strong programming skills in Python, Go or TypeScript
Solid grounding in data structures, algorithms and systems
Experience with APIs, SQL or NoSQL databases and cloud platforms
Curiosity about AI and an interest in startups
Excited to work in person in San Francisco

Why Mercor

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

Compensation and Benefits

$10K housing bonus if you live within 0.5 miles of our office during your internship
$1.5K monthly stipend for meals/rideshare
Health, dental and vision insurance
401(k) eligibility

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Role	Company	Location	Season	Posted
Research Intern	Mercor	San FranciscoOn-site	Summer 2027	8 days ago
Data Science Intern	Mercor	San FranciscoOn-site	Summer 2027	2 months ago
Software Engineer Intern	Mercor	San FranciscoOn-site	Summer 2027	2 months ago