Azure Gpu Compute

Azure Gpu Compute Engineer Jobs

2 jobs found

1mo ago

Machine Learning Engineer

Molex Austin, TX

Austin, TX

1mo ago Closed

$170k - $250k/yr Full time Python Artificial Intelligence Azure Gpu Compute

This position is no longer accepting applications (closed Sep 27, 2026).

Job Description

Molex is hiring a Machine Learning Engineer for an Austin, TX onsite role. This position focuses on building physics-informed surrogate models on Azure Machine Learning to predict engineering simulation outcomes from design parameters. The result is faster iteration and reduced reliance on full high-fidelity simulation, with models deployed, monitored, and improved over time.

Compensation: USD 170,000 - 250,000 per yearly

Experience: 10+ years

What you will be doing

Design and train surrogate models using approaches such as neural networks, Gaussian processes, gradient-boosted trees, and GNNs/PINNs on Azure GPU compute (ND/NC series).
Incorporate physics-informed constraints so predictions remain physically valid rather than purely statistical fits.
Create uncertainty and confidence scoring to determine which designs require full simulation validation, then retrain as new results arrive.
Deploy and version models through Azure ML endpoints and the model registry, with ongoing rolling drift monitoring.
Benchmark surrogate performance against full simulation to quantify speedups and support platform-level performance tuning.

What you will need

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

Benefits

Medical, dental, and vision coverage
Flexible spending and health savings accounts
Life insurance
AD&D (ADD) and disability coverage
Retirement benefits
Paid vacation/time off
Educational assistance
May include infertility assistance
Paid parental leave and adoption assistance

What will put you ahead

Direct experience with industry-standard EM or physics simulation tools
Geometric deep learning experience, including graph neural networks and mesh-based models for CAD data
Background in RF/high-speed electronics or interconnect design

View full job page →

1mo ago

Machine Learning Engineer

Molex Lisle, IL

Lisle, IL

1mo ago Closed

$170k - $250k/yr Full time Python Artificial Intelligence Azure Gpu Compute

This position is no longer accepting applications (closed Sep 23, 2026).

Job Description

Work onsite in Lisle, IL to accelerate engineering design cycles by delivering physics-informed machine learning surrogates on Azure.

Responsibilities

Design and train surrogate models, including neural networks, Gaussian processes, gradient-boosted trees, and GNNs/PINNs
Train on Azure GPU compute using ND/NC series resources
Apply physics-informed constraints to keep predictions physically valid, beyond purely statistical fit
Create model-uncertainty and confidence scoring to determine which candidate designs require full simulation validation
Retrain surrogate models as new simulation results become available
Deploy and manage model lifecycle using Azure ML endpoints and model registry
Monitor deployed models for drift on a rolling basis
Benchmark surrogate runtime versus full simulation to guide platform-level performance tuning
Partner with data scientists and MLOps teams to productionize and operationalize model workflows

Requirements

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

Technologies

Azure Machine Learning
Azure GPU compute (ND/NC series)
Python
PyTorch
TensorFlow
Azure ML endpoints
Model registry
Neural networks
Gaussian processes
Gradient-boosted trees
GNNs
PINNs
Bayesian approaches
Ensembling
GPU-heavy training

Benefits

Medical, dental, and vision coverage
Flexible spending and health savings accounts
Life insurance
ADD
Disability coverage
Retirement benefits
Paid vacation/time off
Educational assistance
May also include infertility assistance
Paid parental leave
Adoption assistance

Who You’ll Work With (Highlights)

Data scientists and MLOps teams

Who Will Put You Ahead

Direct experience with industry-standard EM or physics simulation tools
Geometric deep learning experience, including graph neural networks and mesh-based models for CAD data
Background in RF/high-speed electronics or interconnect design

Location: Lisle, IL 60532 (onsite)

Compensation: USD 170,000 - 250,000 per year

Experience: 10+ years

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