Founding RL Engineer

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Founding RL Engineer (San Francisco, on-site, full-time)
About the role
We are looking for a Founding Reinforcement Learning Engineer to build the core RL systems from the ground up. You will work directly with the founders, own the full loop from environment design to training to evaluation, and help shape the technical direction of the company.
What you will do
Design and build RL environments, reward functions and training pipelines
Train and fine-tune models with RL methods (PPO, GRPO, DPO, RLHF / RLAIF and similar)
Build evaluation frameworks to measure model and agent performance
Run experiments fast, read results, and decide what to try next
Scale training on GPU clusters and keep pipelines reliable
Turn research ideas into production systems
Help set engineering culture and hire the next engineers
What we are looking for
2+ years of hands-on experience in reinforcement learning or ML engineering
Strong Python skills and deep experience with PyTorch (or JAX)
Hands-on work training models with RL (policy gradient methods, reward modeling, RLHF or similar)
Experience with LLM post-training or agent training is a big plus
Comfortable with distributed training and GPU infrastructure
Builder mindset: you ship fast and are happy in a small, early team
Degree in CS, Math, Physics or a related field (MS / PhD a plus)
Nice to have
Publications or open-source work in RL
Experience at an AI lab or an early-stage AI startup
Experience with simulation or environment frameworks (Gymnasium, Ray RLlib, Isaac, MuJoCo)
Experience with training libraries like TRL, verl or OpenRLHF
Details
Location: San Francisco, CA (on-site)
Employment type: Full-time
Compensation: $125,000 - $200,000 USD

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