Co-designed chips, racks, and software to push the pareto frontier to best-in-class throughput and interactivity. Backed by Kleiner Perkins and Sequoia.
About the role
As a research lead, you will set the research direction for this effort and spearhead the development of self-improving agents that reliably complete difficult, long-running engineering tasks. At Etched, this loop compounds: better agents help us build and optimize our systems faster, better systems expand our capacity to run more experiments, generating feedback and training data that further improve agent capabilities. Your job is to make this loop work in practice.
What they're looking for
- Strong research taste and a record of turning ambiguous problems into clear hypotheses, decisive experiments, and useful systems
- Excellent engineering ability. You can move between research exploration, agent experimentation, low-level debugging, and production execution, and you take responsibility for systems working reliably
- Experience building agents for complex, multi-step tasks, with a practical understanding of context, memory, tools, evaluation, and failure recovery
- Hands-on experience with LLM post-training, including SFT and RL
- A track record of making meaningful progress under compute and data constraints. You care about the quality of the experiment and the cost of a successful outcome
- High agency and comfort with unfamiliar domains. You can find the problem, acquire the missing context, and drive the work forward
More about this role
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.
As a research lead, you will set the research direction for this effort and spearhead the development of self-improving agents that reliably complete difficult, long-running engineering tasks. At Etched, this loop compounds: better agents help us build and optimize our systems faster, better systems expand our capacity to run more experiments, generating feedback and training data that further improve agent capabilities. Your job is to make this loop work in practice.
This requires strong research judgment. Where will better memory, context, or tooling unlock new capabilities? Which tasks benefit from structured workflows, and which require more open-ended autonomy? When do agent limitations call for changes to the harness, and when do they require custom...
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