Research Intern

Mercor
San Francisco, CA
On-siteCareer-pivot friendly

Who this role is best for

Candidates with advanced quantitative degrees and experience in model evaluation will find this research-intensive role in San Francisco.

Best fit for

  • Candidates with advanced quantitative degrees and experience in model evaluation
    — “Currently pursuing a master’s or PhD in computer science, machine learning, statistics, mathematics, or another relevant field.”
  • Individuals with a background in reinforcement learning or reward modeling techniques
    — “Study reward-shaping and post-training methods, including approaches such as GRPO and DAPO.”
  • Those comfortable with high-impact, collaborative projects in AI research
    — “Work closely with research scientists, research engineers, and domain experts to turn open-ended questions into rigorous experiments.”

Things to consider

  • In-person work is required in San Francisco, NYC, or London.
    — “We work in-person five days a week in our San Francisco, NYC, or London offices.”
  • The role demands a high degree of ownership and rapid iteration.
    — “Comfort operating in a fast-paced research environment with rapid iteration and a high degree of ownership.”

How to stand out

  • Highlight contributions to open-source projects or research papers in your resume.
    — “At least one publication or open source project.”
  • Demonstrate experience in designing evaluation methodologies or benchmarks.
    — “Developing benchmarks, evaluation methodologies, or data-quality measures.”
  • Showcase your ability to conduct systematic failure analysis and draw actionable insights.
    — “Conduct systematic error analysis to identify model failure modes and opportunities for improvement.”
  • Emphasize your experience with Python-based research code and data pipelines.
    — “Strong programming skills, particularly in Python, and the ability to write reliable research code.”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Individual

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Develop and investigate research questions
  • Design and run controlled experiments
  • Contribute to research publications
Typical background
Currently pursuing a master’s or PhD in computer science, machine learning, statistics, mathematics

Skills & requirements

Required

Research Experience In Post-training, Rlvr, Data Generation, And Model EvaluationExperience In Training, Fine-tuning, Or Evaluating Language Models

Preferred

Experience With Agentic AI Systems, RL EnvironmentsDeveloping Benchmarks, Evaluation Methodologies

Stack & domain

Post-trainingReinforcement Learning With Verifiable Rewards (rlvr)Data GenerationModel EvaluationControlled ExperimentsEvaluation MethodologiesSystematic Failure AnalysisTool UseAgentic BehaviorReal-world ReasoningResearch QuestionsExperimentsData QualityPerformance UpliftBenchmarksResearch ToolingData PipelinesResearch PublicationsBenchmark ReleasesAI SystemsRL EnvironmentsGRPODAPOLeadershipCommunicationTeamworkProblem-solvingNegotiationStrategic ThinkingCustomer ServiceProject ManagementTime ManagementAdaptabilityCreativityEmpathyResearchAIMachine LearningStatisticsMathematics

About the role

Original posting from Mercor via Ashby

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.

Source: Mercor careers (Ashby)

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