Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build AI agents that turn hardware requirements into verified, manufacturable electrical and mechanical designs. You will integrate CAD, EDA, and simulation tools; develop agent workflows and evaluations; curate feedback datasets; run reproducible experiments; and ship and measure agent-generated hardware designs.
Requirements
- Experience building and shipping LLM-based agents or AI tooling
- Context engineering, tool integration, orchestration, evaluation, and failure analysis experience
- Strong software-engineering skills, especially Python
- Interest, experience, or academic exposure in electrical or mechanical engineering, or demonstrated ability to learn a technical domain deeply
- Ability to reason about physical constraints and distinguish plausible designs from verified designs
- Experience using AI for learning and new problems, including agentic coding tools, deep research, and frontier models
- An evaluation-driven approach to measuring and improving AI systems
- Ability to work across research exploration, agentic experimentation, engineering-tool debugging, and production execution
Responsibilities
- Build AI systems that turn engineering requirements into verified electrical and mechanical designs through manufacturing outputs
- Build agents that operate CAD, EDA, and simulation tools to generate designs, run experiments, inspect results, diagnose problems, and iterate
- Develop workflows for component selection, schematic capture, PCB layout, mechanical CAD, assemblies, thermal analysis, and electrical and structural simulation
- Build tool integrations and representations for geometry, connectivity, materials, tolerances, and coupled engineering constraints
- Design evaluations for engineering correctness, constraint satisfaction, simulation accuracy, manufacturability, and performance
- Turn simulation outputs, design-rule checks, engineering reviews, and physical measurements into structured model feedback
- Curate datasets and design memory from trajectories, demonstrations, failures, and manufactured outcomes
- Build reproducible experiment infrastructure for traceable, scalable design experiments
- Ship agent-generated designs and quantify improvements in design cycle time, hardware performance, and engineering effort
- Evaluate and deploy models and methods for each design-loop stage
Benefits
- Medical, dental, and vision coverage
- USD 500 monthly credit for waiving medical benefits
- USD 2,500 monthly housing subsidy for employees living within walking distance of the office
- Relocation support to San Jose
- Wellness benefits covering fitness and mental health
- Daily office lunch and dinner
- Unlimited compute budget subject to ROI justification