Applied AI Engineer - Hardware

Etched builds an inference-focused frontier AI system that helps translate engineering intent into verified, manufacturable hardware. You will work on AI agent systems that connect electrical and mechanical requirements to real design outputs, using tool-integrated workflows, simulations, and evaluations to drive measurable improvements in design quality and cycle time. This is a fully in-person role in San Jose, CA (onsite).

What you’ll do

• Build and own AI systems that convert engineering requirements into verified electrical and mechanical designs, carrying constraints from early concepts through manufacturing outputs.
• Create agents that operate CAD, EDA, and simulation tools to generate designs, run experiments, inspect results, diagnose issues, and iterate with your teams to the limits of model autonomy.
• Develop end-to-end workflows covering component selection, schematic capture, PCB layout, mechanical CAD, assemblies, thermal analysis, and electrical and structural simulation.
• Build the tool integrations and representations agents need to reason about geometry, connectivity, materials, and tolerances, including coupled electrical, mechanical, thermal, and manufacturing constraints.
• Design evaluation plans to measure engineering correctness, constraint satisfaction, simulation accuracy, manufacturability, and performance on real design tasks.
• Convert simulation results, design-rule checks, engineering reviews, and physical measurements into structured feedback models that can learn from them.
• Curate proprietary datasets and design memory from complete trajectories, expert demonstrations, failed approaches, and manufactured outcomes.
• Build reproducible experiment infrastructure so revisions, tool actions, simulation settings, and results are traceable and can run at scale.
• Ship agent-generated designs with electrical, mechanical, and manufacturing teams, and quantify improvements in design cycle time, hardware performance, and engineering effort.
• Continuously evaluate new model releases and deploy the best models and methods for each stage of the design loop.

What you bring

• A track record of solving hard problems across stacks and domains, with comfort in unfamiliar territory.
• Hands-on experience building and shipping LLM-based agents or AI tooling people rely on, including context engineering, tool integration, orchestration, evaluation, and failure analysis.
• Strong Python engineering skills, including the ability to build reliable integrations with complex engineering tools, debug unknown systems, and guide AI to write code well (the focus is on shipping working systems).
• Interest, experience, or academic exposure in electrical or mechanical engineering, or demonstrated learning depth sufficient to build useful tools for practitioners, including the ability to reason about physical constraints and differentiate plausible from verified designs.
• Fluency using AI to learn and ramp on new problems through agentic coding tools, deep research, and frontier models.
• An eval-driven mindset that includes measuring performance, investigating failures, and using those results to improve systems.
• Comfort moving between research exploration, agentic experimentation, engineering-tool debugging, and production execution.

Tech you’ll work with

• Python, LLM-based agents, CAD, EDA, simulation
• Agentic coding tools, deep research
• Transformer and transformer-like architectures

Compensation and benefits

Base compensation: $150,000 - $250,000 per year, plus significant equity.

• 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)
• Wellness benefits covering fitness, mental health, and more
• Daily lunch and dinner in our office
• Unlimited compute budget subject to ROI justification
• Plus significant equity

How Etched works

• Believes in the Bitter Lesson.
• Is an inference-focused frontier AI system, betting early on transformer and transformer-like architectures and increasing model sizes.
• Is fully in-person in San Jose (Santana Row) and values engineering skills.
• Has no boundaries between engineering and research, with technical staff expected to contribute across disciplines as needed.

Nice-to-haves

• High agency and comfort with ambiguity
• Automating CAD or EDA tools through APIs, scripting, plugins, or GUI interaction
• Schematic design, PCB layout, component selection, power delivery, or signal and power integrity
• Parametric CAD, mechanical assemblies, tolerance analysis, thermal management, CFD, or FEA
• Design optimization, constraint solving, or search over large engineering design spaces
• Fine-tuning or post-training models using tool-use trajectories, simulation feedback, or expert demonstrations
• Multimodal reasoning over engineering drawings, schematics, geometry, and simulation results
• Experience taking hardware through fabrication, assembly, bring-up, and testing, and understanding where simulation and physical behavior diverge