In-Person Research Engineer Intern: AI Data & Evaluation

Mercor; San Francisco (CA); On-site; USD 150,000 - 240,000; Full time

Benefits offered by this job

Health benefits

Meals stipend

Relocation & housing support

Equinox membership

Laundry reimbursement

Wellness reimbursement

Job summary

Mercor is hiring a Research Engineer to work at the intersection of engineering and applied AI research in our San Francisco offices. You will contribute to post-training and RLVR, synthetic data generation, and large-scale evaluation workflows that shape how frontier language models learn and improve.

You will help design datasets, build scalable data augmentation pipelines, and develop evaluators and rubrics to drive better model performance while collaborating with researchers and AI teams

Qualifications

• Strong applied research background, with a focus on post-training and/or model evaluation.
• Strong coding proficiency and hands-on experience with machine learning models.
• Strong understanding of data structures, algorithms, backend systems, and core engineering fundamentals.
• Familiarity with APIs, SQL/NoSQL databases, and cloud platforms.
• Ability to reason deeply about model behavior, experimental results, and data quality.
• Excitement to work in person in San Francisco, five days a week, in a fast-paced, high-ownership environment.

Responsibilities

• Work on post-training and RLVR pipelines to understand how datasets, rewards, and training strategies impact model performance.
• Design and run reward-shaping experiments and algorithmic improvements (e.g., GRPO, DAPO) to improve LLM tool-use, agentic behavior, and real-world reasoning.
• Quantify data usability, quality, and performance uplift on key benchmarks.
• Build and maintain data generation and augmentation pipelines that scale with training needs.
• Create and refine rubrics, evaluators, and scoring frameworks that guide training and evaluation decisions.
• Build and operate LLM evaluation systems, benchmarks, and metrics at scale.
• Collaborate closely with AI researchers, applied AI teams, and experts producing training data.
• Operate in a fast-paced, experimental research environment with rapid iteration cycles and high ownership.

Tools

SQL/NoSQL

APIs

Job description

Mercor is hiring a Research Engineer to work at the intersection of engineering and applied AI research in our San Francisco offices. You will contribute to post-training and RLVR, synthetic data generation, and large-scale evaluation workflows that shape how frontier language models learn and improve.

You will help design datasets, build scalable data augmentation pipelines, and develop evaluators and rubrics to drive better model performance while collaborating with researchers and AI teams