Research Scientist; ICML

The Role

Your job is to prove that our data works
. You will design and run training experiments that isolate the impact of our datasets on model behavior. This includes SFT and RL-based post-training, where you'll measure how different data sources shift capability, generalization, and alignment. Working closely with partner labs, you will turn our datasets into clear, defensible evidence:
this data this improvement under these conditions
. This is experimental, high-leverage work.

• Run controlled SFT and RL experiments to measure the impact of our datasets on model performance.
• Help build public evals and new data types that push the frontier.
• Publish external-facing research, blog posts, and technical reports.
• Work with internal SPLs to iterate on data quality based on your results.

• 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).

• Annual target cash compensation of $250-450K + meaningful equity
• Comprehensive benefits (Uber Eats and ride share stipend, comped Equinox, 401K with match, health, dental, and vision insurance)