Internal Acceleration, Research Engineer (Hardware)

Our Internal Acceleration team’s mandate is to build agents to accelerate the production of frontier tokens.

You’ll work directly with our founders and embed with our hardware team to build new agentic harnesses and operating systems to transform the way hardware is built in an AI native world. You’ll work on harnesses, tool use, context, and memory, execution environments, and evals that let agents conduct long-running engineering work that is useful.

This role is for engineers who thrive on ambiguity, have real product sense, and want to own problems end to end. It’s a whiteboard for future founders. The problems we solve are time-sensitive and business-critical. This role will not be a 9-5, and the ideal candidate is excited about that.

• Have at least 1-5+ years of experience building and shipping software end to end, ideally at a fast-moving startup

• Have built agents for complex, multi-step tasks that people depend on, beyond calling an API: tool design, long-context management, evals, and failure analysis.

• Are a strong software engineer who has built reliable systems others depend on, such as distributed systems, experiment infrastructure, or developer tooling.

• Use coding agents heavily, read their transcripts closely, and change the system when an agent is confidently wrong.

• Have high agency in unfamiliar domains. You find the real problem and drive it forward.

• Have product sense, design taste, and extreme attention to detail

• Embed with our hardware team to find the highest-leverage bottlenecks, and own each one from first idea to a tool engineers rely on every day.

• Build and deploy LLM agents wired into our engineering workflows via tool-calling and MCP.

• Build execution environments where agents can verify their own work, with sandboxed access to simulators, EDA flows, compilers, profilers, and real hardware.

• Ship full-stack internal products from zero to one: the interfaces, data pipelines, and infrastructure that define how Etched builds.

• Measure what works. Design evals and track adoption so we double down on the tools that matter and kill the ones that don’t.

• Take on special projects directly with the founders, surfacing problems across the company and doing whatever it takes to hit critical milestones.

• Exposure to chip development, kernels, hardware, or manufacturing.

• Infrastructure, data engineering, or DevOps experience

• Fine-tuning, RAG over proprietary technical data, or multi-agent orchestration

• Startup experience, especially through hypergrowth

• 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

• $150K – $400K+

• Plus Significant Equity

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.

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.