Machine Learning Engineer (Physics-based)

Role Description

Root Access is hiring a Machine Learning Engineer to develop models that predict and optimize the behavior of electronic systems. You will build automated simulation pipelines, generate training datasets, and develop models grounded in electrical, thermal, and electromagnetic physics. Working across our hardware and machine learning teams, you will turn engineering simulations and physical measurements into tools that accelerate electronics development.

Responsibilities

• Build and scale automated workflows for electrical, thermal, and electromagnetic simulations.

• Develop surrogate models that approximate physics simulations with faster inference.

• Create training datasets from simulations and hardware measurements.

• Incorporate physical constraints and engineering knowledge into model architectures, training, and evaluation.

• Validate model predictions against established solvers and experimental results.

• Develop active learning and optimization workflows to identify promising designs and prioritize simulations.