Research Scientist - Post Training
Design and run SFT/RL experiments to measure dataset impact on LLM performance, capabilities, and alignment. Collaborate with labs to provide evidence of improvements; requires strong LLM training knowledge and fast experimentation, ideally undergrad/master's research background.
About the job
What You'll Do
- Run controlled SFT and RL experiments to measure the impact of our datasets on model performance.
- Quantify lift across capabilities (reasoning, tool use, long-horizon tasks, domain-specific workflows).
- Communicate your findings with partner labs to help drive sales.
- Work with internal SPLs to iterate on data quality based on your results.
What We're Looking For
- Strong familiarity with LLM training and evaluation methodologies.
- Genuine obsession with how data structure, selection, and quality drive model behavior.
- Ability to design lightweight experiments, move fast, and extract actionable insights from messy results.
- Comfort working across domains (you'll touch finance, software engineering, policy, and more).
- A bias toward building over theorizing.
- Great candidates are undergrad research or master's research (but haven't done a phd).
Compensation Structure
$250k-450k total compensation + equity
Skills
Llm Training, Sft, Rl, Model Evaluation, PyTorch, Hugging Face, Experiment Design, Data Quality, Reasoning Capabilities, Tool Use
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