Azure GPU MLOps Engineer — Scale AI Compute

Molex; Fremont (CA); On-site; USD 200,000 - 280,000; Full time

Benefits offered by this job

Medical

Dental

Vision

Retirement

Paid vacation/time off

Educational assistance

Infertility assistance

Paid parental leave

Job summary

Molex is seeking an experienced GPU- MLOps Engineer to own the Azure platform layer end-to-end, deploying AI/ML models, provisioning and managing GPU compute, and securing the environment. You will optimize costs for our engineering AI/ML platform and work with data scientists, ML engineers, and LLM engineers.

In this role, you will build CI/CD pipelines, scale Azure GPU compute, automate retraining, and enforce access control and secrets management across the stack.

Qualifications

• 10+ years in MLOps, DevOps, or Cloud Infrastructure.
• Strong Azure experience - GPU compute (ND/NC), AKS, containerization (Docker).
• Infrastructure-as-code experience (Terraform or Bicep).
• Solid grasp of cloud security fundamentals (IAM, network security, secrets management).
• Demonstrated experience with cloud cost optimization (right-sizing, autoscaling, spot/preemptible).
• Hands-on experience with model registries and experiment tracking (Azure ML + MLflow).

Responsibilities

• Build and maintain CI/CD pipelines (Azure DevOps) for training, validation, versioning, and deployment of ML models.
• Provision and scale Azure GPU compute (ND/NC) and container infrastructure (AKS/ACI) for training and simulation workloads.
• Automate retraining/redeployment workflows in Azure ML pipelines as new data becomes available.
• Implement access control, identity management, and secrets management (Microsoft Entra ID, Azure Key Vault) across compute, data, and model artifacts.
• Monitor and optimize GPU/cloud spend (Azure Cost Management) and build cost visibility dashboards in Power BI.

Skills

MLOps

DevOps

Cloud Infrastructure

Azure

Azure GPU

AKS

Docker

Terraform

Security

Cost Optimization

Tools

Azure ML

MLflow

Terraform

Job description

Molex is seeking an experienced GPU- MLOps Engineer to own the Azure platform layer end-to-end, deploying AI/ML models, provisioning and managing GPU compute, and securing the environment. You will optimize costs for our engineering AI/ML platform and work with data scientists, ML engineers, and LLM engineers.

In this role, you will build CI/CD pipelines, scale Azure GPU compute, automate retraining, and enforce access control and secrets management across the stack.