Electronic Design Automation

Electronic Design Automation Engineer Jobs

2 jobs found

Today

Applied AI Engineer - Hardware

Etched San Jose, CA

San Jose, CA

Today

$150k - $250k/yr Full time Agentic Ai Ai Agent Ai Engineer

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Job Description

Etched builds an inference-focused frontier AI platform for translating engineering intent into verified, manufacturable hardware designs. This fully in-person role in San Jose (Santana Row) pairs agentic AI tooling with deep engineering collaboration, with no hard boundaries between engineering and research. You will help ship end-to-end workflows where model evaluations, tool integrations, and simulation-driven iterations directly improve real hardware outcomes.

Compensation: USD 150,000 - 250,000 per year plus Significant Equity.

What you’ll do

Build and own AI systems that convert engineering requirements into verified electrical and mechanical designs, carrying intent and constraints from early concepts through manufacturing outputs.
Create agents that use CAD, EDA, and simulation tools to generate designs, run experiments, inspect results, diagnose issues, and iterate with teams to the limits of model autonomy.
Develop 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, tolerances, and coupled electrical, mechanical, thermal, and manufacturing constraints.
Design evaluation methods that measure engineering correctness, constraint satisfaction, simulation accuracy, manufacturability, and performance on real design tasks.
Convert simulation outputs, 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.
Implement reproducible experiment infrastructure so 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 getting dropped into unfamiliar territory.
Hands-on experience building and shipping LLM-based agents or AI tooling people depend on, including context engineering, tool integration, orchestration, evaluation, and failure analysis.
Strong software engineering skills, especially in Python, with the ability to build reliable integrations with complex engineering tools and direct AI to write code that ships.
Interest, experience, or academic exposure to electrical or mechanical engineering, with the ability to reason about physical constraints and distinguish plausible designs from verified ones.
Fluency using AI to learn and ramp on new problems, including agentic coding tools, deep research, and frontier models.
An eval-driven mindset: measuring system performance, investigating failure modes, and using those findings to improve.
Comfort moving across research exploration, agentic experimentation, engineering-tool debugging, and production execution.

Helpful background (nice-to-have)

High agency and comfort with ambiguity.
Automating CAD or EDA tools via APIs, scripting, plugins, or GUI interaction.
Experience with 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.

Technologies you’ll work with

Python
LLM-based agents
CAD, EDA
Simulation
Agentic coding tools
Deep research
Transformer and transformer-like architectures

Benefits

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
Significant equity

How Etched is different: Etched believes in the Bitter Lesson, is an inference-focused frontier AI team, runs a fully in-person organization in San Jose (Santana Row), and expects technical staff to contribute across engineering and research as needed.

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1d ago

Applied Machine Learning Engineer - AI for VLSI Design

NVIDIA Santa Clara, CA

Santa Clara, CA

1d ago

$152k - $265k/yr Full time Electrical Engineering Artificial Intelligence Circuit Design

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Job Description

NVIDIA’s Circuit Solutions Group is building AI-driven software systems that support VLSI and circuit design. In this hybrid role in Santa Clara, CA, you will contribute to frontier EDA initiatives by applying machine learning to real design workflows, with the flexibility to collaborate across research and product teams. The position offers USD 152,000 - 264,500 per year and you will be eligible for equity and benefits.

What you’ll do

You will work inside a multi-functional team delivering results across Pre-silicon and Post-silicon custom circuit design, along with the data and optimization loops that connect them. Your focus will include Circuit/Layout Optimization and Spice correlation, partnering with others to improve design outcomes.

Research and implement techniques that represent frontier solutions in electronic design automation.
Design, build, and iterate agentic AI solutions for VLSI design problems.
Analyze problems and/or datasets, raise and validate hypotheses, and develop models and algorithms until they achieve the desired QOR.

What you bring

MS (or equivalent experience) with 3+ years of experience, or PhD with 1+ years in Electrical/Computer Engineering.
Strict requirement: experience in Combinatorial Optimization, Agentic AI and large language models, and Machine Learning for Chip Design & EDA.
Experience in Algorithms/Data Structures/Applied Math/Machine Learning/Software programming, including proven ability to write code in Python and C++.
Experience in Applied Math/Machine Learning/Software programming, including proven ability to write code in Python and C++.

Preferred ways to stand out

Prior experience in large-scale EDA software development is a plus.
Prior experience in CMOS layout drawing, including schematic-to-layout translation and DRC/LVS compliance, is a definite plus.
Comfort working across multiple levels and teams spanning engineering/research, product, sales, and marketing.
Effective verbal and written communication and technical presentation skills.
Self-starter who enjoys continuous learning and sharing findings with the team.

Technologies: Python, C++

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Electronic Design Automation Engineer Jobs

Applied AI Engineer - Hardware

Applied Machine Learning Engineer - AI for VLSI Design

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