Etched · San Jose
JOB SUMMARY Etched is building AI systems that accelerate its own development. As a Research Engineer on the RL Frontiers team, you will train our proprietary frontier models to automate kernel development, ASIC engineering, production pipelines, and 3-D hardware operating systems. You will use our proprietary simulators and environments to create custom data mixes and post-train models to SOTA performance on our hardest engineering tasks. KEY RESPONSIBILITIES - Own the post-training stack completely end to end. - Build RL environments with ASIC, kernel, and supercomputing engineers, rewarded by simulation, formal tools, tests, and hardware measurements. - Create custom data mixes that unlock frontier performance on relevant tasks. - Create benchmarks that drive real productivity in the models and avoid reward hacking YOU MAY BE A GOOD FIT IF YOU - Have hands-on post-training experience, including SFT and RL (e.g., PPO, GRPO), and have shipped models people used. - Have taken a model from bad to good on a task it wasn’t built for, ideally with scarce data, for example as an early post-training hire at an applied AI company. - Are a strong PyTorch and distributed-training engineer who reads the rollouts and checks the numbers before trusting a result. - Understand the systems side of RL well enough to make the loop faster and cheaper, not just better. - Are entrepreneurial and make good calls under compute and data constraints. Former founders are a plus. STRONG CANDIDATES MAY ALSO HAVE EXPERIENCE WITH - RL or post-training frameworks (e.g., verl, OpenRLHF, TRL, prime-rl) or inference engines (vLLM, SGLang). - Agentic, multi-turn RL with verifiable rewards. - Distillation and training small, specialized models for production. - ASIC design or verification, accelerator kernels, or large-scale compute infrastructure. BENEFITS - Medical, dental, and vision packages with generous premium coverage - $500 per month credit for waiving medical benefits - Housing subsidy of $…
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