Founding RL Engineer – Build Core RL Systems (SF)

Clera Labs, Inc.; San Francisco (CA); On-site; USD 125,000 - 200,000; Full time

Job summary

Clera Labs, Inc. is seeking a Founding Reinforcement Learning Engineer in San Francisco for an on-site, full-time role. You will build core RL systems from the ground up, collaborating directly with the founders to design environments, training loops, and evaluation frameworks.

You will ship fast in a small, early-stage team, scale GPU training, and help set engineering culture while turning research ideas into production. Compensation ranges from $125,000 to $200,000 USD.

Qualifications

• 2+ years of hands-on experience in reinforcement learning or ML engineering.
• Strong Python skills and deep experience with PyTorch.
• Hands-on experience training models with RL (policy gradient methods, 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 in a small, early-stage team.
• Degree in CS, Math, Physics or a related field (MS / PhD a plus).

Responsibilities

• 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.

Skills

Reinforcement learning

Python

PyTorch

RL training

Distributed training

GPU infrastructure

ML engineering

Education

CS/Math/Physics

MS/PhD a plus

Tools

Gymnasium

Ray RLlib

MuJoCo

Isaac

TRL/OpenRLHF

Job description

Clera Labs, Inc. is seeking a Founding Reinforcement Learning Engineer in San Francisco for an on-site, full-time role. You will build core RL systems from the ground up, collaborating directly with the founders to design environments, training loops, and evaluation frameworks.

You will ship fast in a small, early-stage team, scale GPU training, and help set engineering culture while turning research ideas into production. Compensation ranges from $125,000 to $200,000 USD.