Experience Senior · 6+ yrs (5+ years)
About the role
from listingABOUT HILLCLIMB
Hillclimb's mission is to improve agent capabilities towards recursive self-improvement. To do so, we work on creating environments and evals that test and push frontier models' ability to ideate, experiment, and produce impactful research.
We're a founding team of former DeepMind & quant researchers, backed by Tier 1 VCs, Jeff Dean, Paul Graham, Amjad Masad, and angel investors from OpenAI, Anthropic, DeepMind, xAI & Meta Superintelligence Labs.
ABOUT THIS ROLE:
Your work will consist of the following and many more:
- Turn ML research problems into environments that reward a model for real progress and good research taste
- Test whether each environment's reward is repeatable and tracks the quality of the work it scores
- Build systems that create environments at scale and catch broken ones before they reach training
- Run post-training experiments to find which environments are trainable
PREFERRED EXPERIENCE:
- Prior experience with LLMs, RL, RLHF/RLAIF, RLVR, post-training, evals, graders, synthetic data, model training, or coding agents at a frontier/data lab
- Understanding of what makes a reward evaluation trustworthy, and how models exploit one that is not
- Background in designing automated systems for building, validating, and quality checking environments.
BENEFITS:
- Health, dental, vision insurance
- Competitive 401k match
- Free lunch & dinner