Research Engineer, RL Frontiers

Posted 11 Hours Ago
Be an Early Applicant
San Jose, CA, USA
In-Office
400K-400K Annually
Entry level
Artificial Intelligence • Hardware • Software
The Role
Train and post-train frontier models for engineering tasks, owning the post-training stack end to end. Build reinforcement-learning environments and verifiable reward systems with ASIC, kernel, and supercomputing engineers; develop custom data mixes, benchmarks, and specialized production models. Optimize RL systems for speed and cost while validating rollouts and performance metrics. The role is fully in person in San Jose.
Summary Generated by Built In
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 $2,500 per month for those living within walking distance of the office

  • Relocation support for those moving to San Jose (Santana Row)

  • Various wellness benefits covering fitness, mental health, and more

  • Daily lunch and dinner in our office

  • Unlimited compute budget subject to ROI justification

Base Compensation Range
  • $400K+

  • Plus Significant Equity

How we’re different

Etched believes in the Bitter Lesson. We are the first inference-focused frontier AI system, betting early on transformer and transformer-like architectures and on increasing model sizes. Our addressable market is the entirety of inference, unlike many of our competitors.

We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.

About Etched

Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history.

Skills Required

  • Hands-on post-training experience, including supervised fine-tuning and reinforcement learning such as PPO or GRPO
  • Experience shipping models that people used
  • Experience improving a model on a task it was not originally built for, preferably with scarce data
  • Strong PyTorch and distributed-training engineering skills
  • Ability to inspect rollouts and validate performance metrics
  • Understanding of reinforcement-learning systems and how to improve loop speed and cost
  • Entrepreneurial judgment and ability to make decisions under compute and data constraints
  • Experience with reinforcement-learning or post-training frameworks such as verl, OpenRLHF, TRL, or prime-rl
  • Experience with inference engines such as vLLM or SGLang
  • Experience with agentic, multi-turn reinforcement learning and verifiable rewards
  • Experience with distillation and training small specialized production models
  • Experience with ASIC design or verification, accelerator kernels, or large-scale compute infrastructure
  • Former founder experience

Etched Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Etched and has not been reviewed or approved by Etched.

  • Equity Value & Accessibility — Equity growth is described as strong and significant equity is part of the package. High total compensation for technical roles reinforces the equity-led upside.
  • Healthcare Strength — Medical, dental, and vision coverage include generous premium support, indicating robust core healthcare. This reduces employee cost exposure for essential coverage.
  • Wellbeing & Lifestyle Benefits — Daily lunch and dinner, a housing subsidy for those living near the office, relocation support, and wellness perks are highlighted. These offerings lower day-to-day living costs and support practical wellbeing.

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The Company
HQ: Pakenham
53 Employees
Year Founded: 2022

What We Do

By burning the transformer architecture into our chips, we’re creating the world’s most powerful servers for transformer inference.

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