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Research Scientist - RL environments​/METR​/LLM​/RLHF or RLVR

Job in San Francisco, San Francisco County, California, 94102, USA
Listing for: Talent Search PRO
Full Time position
Listed on 2026-07-15
Job specializations:
  • Research/Development
    AI Evaluation, Data Scientist
Salary/Wage Range or Industry Benchmark: 150000 - 250000 USD Yearly USD 150000.00 250000.00 YEAR
Job Description & How to Apply Below
Position: Research Scientist - RL environments / METR / LLM/ RLHF or RLVR

Job Title

Salary: $150,000 - $250,000

What You'll Do

Design data slices and explore data shapes that expose meaningful model failure modes across domains, including finance, code, and enterprise workflows. Build and refine evaluation rubrics and reward signals for RLHF and RLVR training pipelines. Model annotator behavior and run experiments to improve different model capabilities. Develop quantitative frameworks for measuring dataset quality, diversity, and downstream impact on model alignment and capability.

Partner with lab research teams to translate their training objectives into concrete data and evaluation specifications. Move fast from hypothesis to experiment, extract actionable insights from messy results, and iterate quickly.

Requirements

Must-Have

Strong quantitative instincts with familiarity with LLM training pipelines, RLHF or RLVR, or evaluation methodology. Does not need a PhD but must have the research depth of a strong undergrad or master's researcher. Genuine obsession with how data structure, selection, and quality drive model behavior. This is the core of the work and must be intrinsically motivated. Ability to design lightweight experiments, move fast, and extract actionable insights from messy and incomplete results.

Comfort working across domains, the work touches finance, software engineering, policy, and more. Must be able to context-switch and reason clearly across all of them. Bias toward building over theorizing. Ships experiments and iterates, does not get stuck in design.

Nice-to-Have

Prior work or internship at RL environment companies, AI safety organizations, or benchmarking organizations such as METR or Artificial Analysis. Background in evaluation methodology, benchmark design, or dataset curation at a lab or research organization. Exposure to annotator modeling, reward signal design, or alignment-related research.

The standard base is 150 to 250k, but they also engage in profit sharing, so their total cash comp will land between 250 and 450k, and then, of course, there's equity on top of that.

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