Senior ML Engineer: Physics-Informed Surrogates on Azure

Molex; Fremont (CA); On-site; USD 170,000 - 250,000; Full time

Benefits offered by this job

medical

dental

vision

flexible spending and health savings

life insurance

ADD

disability

retirement

paid vacation/time off

educational assistance

infertility assistance

paid parental leave

adoption assistance

Job summary

Molex in the United States seeks an ML Engineer to build physics-informed surrogate models on Azure ML that predict engineering outcomes directly from design parameters. They will pre-screen candidate designs in milliseconds so only the most promising ones require full high-fidelity simulation, accelerating the design-optimization cycle.

You will join the platform team behind our Azure AI/ML engineering tools, collaborating with data scientists, LLM engineers, and MLOps to keep GPU-heavy

Qualifications

• Hands-on experience building, training, and deploying ML models in production.
• Experience with physics-informed ML or surrogate modeling for engineering systems.
• Strong Python programming with PyTorch or TensorFlow.
• Familiar with cloud ML platforms and model deployment concepts.

Responsibilities

• Design and train surrogate models on Azure GPU compute.
• Incorporate physics-informed constraints to ensure valid predictions.
• Build model-uncertainty and confidence scoring to guide full-simulation validation.
• Deploy and version models via Azure ML endpoints and model registry; monitor drift.
• Benchmark surrogate performance against full simulations to guide tuning.

Skills

Python

PyTorch

TensorFlow

Azure ML

uncertainty quantification

_graph neural networks

Tools

Azure Machine Learning

ND/NC series GPUs

model registry

Azure ML endpoints

Job description

Molex in the United States seeks an ML Engineer to build physics-informed surrogate models on Azure ML that predict engineering outcomes directly from design parameters. They will pre-screen candidate designs in milliseconds so only the most promising ones require full high-fidelity simulation, accelerating the design-optimization cycle.

You will join the platform team behind our Azure AI/ML engineering tools, collaborating with data scientists, LLM engineers, and MLOps to keep GPU-heavy