Senior ML Engineer: EDA & Physical AI

Trace; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Trace is seeking a senior ML/EDA-focused engineer to advance neural networks and LLM-driven design tools for PCB workflows. You will develop data pipelines, train and deploy models, and integrate model outputs into real-world design environments.

The role emphasizes handling geometry/graph-based optimization challenges, collaborating with PCB and CAD teams, and delivering production-facing tooling at scale. A strong engineering background and practical experience in quick iteration are essential.

Qualifications

• Bachelor’s degree or higher in a quantitative field (ML/EE/CE/CS/Math/Physics).
• Strong background in machine learning and/or electrical engineering.
• 5+ years of relevant industry experience.
• Proficiency in Python and at least one major ML framework (PyTorch or TensorFlow).
• Experience training, fine-tuning, evaluating, or deploying neural networks, LLMs, or similar systems.
• Experience with AWS and/or GCP for training, data pipelines, or deployment.
• Ability to work on structured, geometric, graph-based, or optimization-heavy problems.
• Comfort building production-facing tools, pipelines, and systems.

Responsibilities

• Build and improve neural network and LLM systems for circuit understanding, placement, routing, and design assistance.
• Create training, fine-tuning, and evaluation pipelines for PCB and schematic data.
• Develop model-driven tooling that integrates into production design workflows.
• Collaborate with PCB, CAD, and product teams to encode design rules into model behavior.
• Prototype and productionize systems for retrieval, ranking, generation, scoring, and design-space exploration.
• Build feedback loops between model outputs, design data, and user actions.
• Define and improve metrics for layout quality, constraint satisfaction, manufacturability, and user value.
• Own projects end to end from data prep and experiments to deployment and iteration.

Skills

Python

ML frameworks (PyTorch/TF)

Neural networks

LLMs

Data pipelines

GPU training workflows

Graph/optimization problems

Production tooling

Education

Bachelor’s or higher in ML/EE/CE/CS/Math/Physics

Master’s degree or higher (preferred)

Tools

AWS

GCP

GPU-based training workflows

Model serving infra

Job description

Trace is seeking a senior ML/EDA-focused engineer to advance neural networks and LLM-driven design tools for PCB workflows. You will develop data pipelines, train and deploy models, and integrate model outputs into real-world design environments.

The role emphasizes handling geometry/graph-based optimization challenges, collaborating with PCB and CAD teams, and delivering production-facing tooling at scale. A strong engineering background and practical experience in quick iteration are essential.