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Etched

Designs chips and servers for running AI models

Research Engineer - RL Frontiers

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Jose, CA, USA$400k

About the Job

Requirements

  • Hands-on post-training experience, including supervised fine-tuning and reinforcement learning such as Proximal Policy Optimization or Group Relative Policy Optimization, and experience shipping models that people used.
  • Experience improving a model's performance on a task it was not built for, ideally with scarce data or as an early post-training hire at an applied AI company.
  • Strong PyTorch and distributed-training engineering skills, including inspecting rollouts and validating results.
  • Understanding of reinforcement-learning systems sufficient to improve the speed and cost of the training loop.
  • Ability to make sound decisions under compute and data constraints.

Responsibilities

  • Train proprietary frontier models to automate kernel development, ASIC engineering, production pipelines, and three-dimensional hardware operating systems.
  • Use proprietary simulators and environments to create custom data mixes and post-train models to state-of-the-art performance on engineering tasks.
  • Own the post-training stack end to end.
  • Build reinforcement-learning environments with ASIC, kernel, and supercomputing engineers, using rewards from simulation, formal tools, tests, and hardware measurements.
  • Create custom data mixes to improve frontier-model performance on relevant tasks.
  • Create benchmarks that drive model productivity and avoid reward hacking.

Desired Qualifications

  • Experience with reinforcement-learning or post-training frameworks such as verl, OpenRLHF, TRL, or prime-rl, or inference engines such as vLLM or SGLang.
  • Experience with agentic, multi-turn reinforcement learning with verifiable rewards.
  • Experience with distillation and training small, specialized models for production.
  • Experience with ASIC design or verification, accelerator kernels, or large-scale compute infrastructure.
  • Former founder experience.

About the Company

Etched

Designs chips and servers for running AI models

Etched designs AI chips and the server racks built around them for AI companies and cloud providers, focusing only on inference, the work of running trained models to answer requests. In 2024, it unveiled a chip hard-wired to run only transformers, the type of AI model behind ChatGPT, after betting at its founding that they would dominate AI. Etched develops its chips, racks, and software together, and each rack links many chips through a shared pool of fast memory so very large models with long inputs can answer quickly. It earns money by selling these complete systems rather than individual chips. Etched was founded in 2022 and is based in San Jose, California.

Company size
201-500
Company stage
Series D
Total funding
$1.6B
Headquarters
San Jose, CA
Founded
2022

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