Machine Learning Engineer

Molex is hiring a Machine Learning Engineer in Austin, TX (onsite) to help reduce reliance on full high-fidelity engineering simulations. This role focuses on building and operationalizing physics-informed surrogate models on Azure Machine Learning, so design teams can predict simulation outcomes from design parameters faster, with uncertainty-aware decisions about when full validation is still needed. The salary range is USD 170,000 - 250,000 per year.

What you’ll build and improve

• Design and train surrogate models using neural networks, Gaussian processes, gradient-boosted trees, and GNNs/PINNs on Azure GPU compute (ND/NC series).
• Apply physics-informed constraints so model outputs remain physically valid, not just statistically accurate.
• Create model uncertainty and confidence scoring to identify which designs require full simulation validation.
• Continuously retrain models as new simulation results arrive, improving performance over time.

Deploy, monitor, and benchmark

• Deploy and version models using Azure ML endpoints and the model registry.
• Monitor models on a rolling basis for drift.
• Benchmark surrogate performance against full simulation to support platform-level performance tuning.

What you bring

• Extensive hands-on production experience building, training, and deploying ML models (not limited to pretrained API usage).
• 10+ years building ML for physical or engineering systems, including surrogate modeling, physics-informed ML, or scientific ML.
• Strong Python skills with PyTorch or TensorFlow.
• Understanding of relevant engineering/physics fundamentals and simulation data formats for your domain.
• Experience with Azure Machine Learning or a similar cloud ML platform.
• Familiarity with uncertainty quantification, including Bayesian approaches and ensembling.

Additional advantages

• Direct experience with industry-standard EM or physics simulation tools.
• Background in geometric deep learning (graph neural networks and mesh-based models) for CAD data.
• Experience in RF/high-speed electronics or interconnect design.

Benefits

• Medical, dental, and vision
• Flexible spending and health savings accounts
• Life insurance
• ADD, disability
• Retirement
• Paid vacation/time off
• Educational assistance
• May also include infertility assistance
• Paid parental leave and adoption assistance