Applied AI Engineer, Kernel Performance

About the 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.

Key Responsibilities

• Own the system that turns new model architectures into verified, production-ready kernels and model mappings.
• Build agents that understand Etched hardware, design experiments, generate implementations, compile and profile them, diagnose bottlenecks, and iterate with our teams, to the limits of model autonomy.
• Design evals covering correctness, numerical stability, latency and efficiency.
• Turn profiler traces, simulation, hardware counters, and expert judgment into structured signals models can learn from.
• Curate proprietary datasets and optimization memory from complete trajectories, expert demonstrations, counterexamples, and production outcomes.
• Build fast, reproducible experiment infrastructure and observability so experiments remain interpretable, trustworthy, and high-throughput.
• Ship model-generated improvements to production and quantify their impact on end-to-end system performance.
• Partner deeply with other architecture teams to shape new abstractions and Etched’s hardware-software roadmap.
• Continuously evaluate new model releases and deploy the best for each stage of the optimization loop.

Qualifications

• A track record of solving hard problems across stacks and domains — you enjoy being dropped into unfamiliar territory and figuring it out.
• Comfort with both Python and low-level code: you can read it, modify it, debug it, and direct AI to write it well. We do not care whether you write code from scratch — we care whether you ship things that work.
• Kernel experience: you've written or tuned kernels and can explain the mechanisms and performance impact of optimizations you’ve shipped.
• Fluency using AI to learn and ramp on new problems — agentic coding tools, deep research, and frontier models are how you work, not an add-on.
• Moving fluidly between research exploration, agentic experimentation, low-level debugging, and production execution.
• Strong Candidates May Also Have Experience:
• First principles thinking on accelerator performance: memory hierarchy, data movement, parallelism, synchronization, and low-precision computation.
• Hands-on experience building and shipping LLM-based agents or AI tooling that real users depend on in production environments (beyond calling an API — context engineering, tool integration, orchestration, failure analysis).
• An eval-driven mindset: you measure whether AI systems work before scaling them.
• Fine-tuning or post-training, RAG over proprietary data, and/or multi-agent orchestration.

Benefits

• Medical, dental, and vision packages with generous premium coverage
• $500 per month credit for waiving medical benefits
• Housing subsidy of $2k per month for those living within walking distance of the office
• Relocation support for those moving to San Jose (Santana Row)
• Variety of wellness benefits covering fitness, mental health, and more
• Daily lunch and dinner in our office
• Unlimited compute budget subject to ROI justification

Pay

Base Compensation Range: $150,000 – $225,000

Schedule

Full-time, in-person position in San Jose (Santana Row)