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Salary: USD 150,000 - 400,000 / annual
Etched is hiring a Research Engineer for the Internal Acceleration team to build AI agents that accelerate the production of frontier inference tokens. You'll work directly with founders and embed with teams building kernels, ASICs, hardware, production, and special projects to create agentic harnesses and operating systems that transform how hardware is built in an AI-native world.
You'll own problems end-to-end, from identifying high-leverage bottlenecks across engineering teams to shipping full-stack internal products. Key responsibilities include:
- Embedding with kernels, ASIC, hardware, and production teams to find and own the highest-leverage bottlenecks, building tools engineers rely on daily
- Building and deploying LLM agents wired into engineering workflows via tool-calling and MCP (Model Context Protocol)
- Creating execution environments where agents can verify their own work with sandboxed access to simulators, EDA flows, compilers, profilers, and real hardware
- Shipping full-stack internal products from zero to one: interfaces, data pipelines, and infrastructure that define how Etched builds
- Designing evals and tracking adoption to identify which tools matter and which to sunset
- Taking on special projects directly with founders to surface cross-company problems and hit critical milestones
This role is for engineers who thrive on ambiguity, have strong product sense, and want to own problems end-to-end. The team is fully in-person in San Jose and values engineering skills highly, with no boundaries between engineering and research. This is not a 9-to-5 role; the ideal candidate is excited about the intensity and time-sensitivity of the work.
Company context: Etched is building hardware for frontier intelligence, co-designing chips, racks, software, and manufacturing to deliver best-in-class throughput and latency for inference workloads. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, the company is redefining the infrastructure layer for AI.
REQUIREMENTS:
- 1–5+ years of experience building and shipping software end-to-end, ideally at a fast-moving startup
- Experience building agents for complex, multi-step tasks beyond simple API calls, including tool design, long-context management, evals, and failure analysis
- Strong software engineering background with experience building reliable systems others depend on (distributed systems, experiment infrastructure, developer tooling)
- Heavy use of coding agents with close attention to transcripts; ability to identify and fix confident errors in agent behavior
- High agency in unfamiliar domains; ability to find the real problem and drive it forward
- Product sense, design taste, and extreme attention to detail
STRONG ADDITIONAL QUALIFICATIONS:
- 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
