Research Intern
Mercor· Research | Internships
San FranciscoInternPosted 2w ago
About the role
Mercor internship position focused on research at the frontier of post-training, reinforcement learning with verifiable rewards (RLVR), data generation, and model evaluation. The role involves designing controlled experiments, developing evaluation methodologies, performing failure analysis, and contributing to publications and benchmarks.
Responsibilities
- 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.
Qualifications
- 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.
Skills
Required:Research design and experimentationPython programmingMachine learning fundamentals
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.
Last updated Oct 7, 2026. Interested? Apply on the company site.
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