GPU MLOps Engineer

This is a fully remote position, open to applicants in California, +2 more states.

📋 Description

• Take full ownership of the Azure platform layer for the engineering AI/ML platform from start to finish.

• Develop and uphold Azure DevOps CI/CD pipelines for the training, validation, versioning, and deployment of ML models.

• Provision and scale Azure GPU compute resources (ND/NC series) and AKS/ACI container infrastructure for training and simulation tasks.

• Streamline model retraining and redeployment processes in Azure ML pipelines as new data becomes available.

• Implement access control, identity management, and secrets management utilizing Microsoft Entra ID and Azure Key Vault.

• Monitor and optimize spending on Azure GPU/cloud services through Azure Cost Management.

• Create cost visibility dashboards using Power BI.

• Collaborate with data scientists, ML engineers, and LLM engineers to ensure smooth platform operations.

⛳️ Requirements

• Over 10 years of experience in MLOps, DevOps, or Cloud Infrastructure, with a focus on ML deployment and cloud infrastructure management.

• Extensive experience with Azure, particularly in GPU compute (ND/NC), Azure Kubernetes Service, and Docker containerization.

• Proficiency in infrastructure-as-code tools like Terraform or Bicep.

• Strong understanding of cloud security principles, including IAM, network security, and secrets management.

• Proven experience in optimizing cloud costs, including strategies for right-sizing, autoscaling, and utilizing spot/preemptible resources.

• Practical experience with model registries and experiment tracking using Azure ML and MLflow.

• Preferred experience with GPU-intensive workloads, such as ML training or HPC simulations.

• Preferred Azure certifications, including Solutions Architect Expert or Security Engineer Associate.

• Experience with HPC job schedulers, such as Slurm via Azure CycleCloud, is preferred.

• Experience in supporting engineering simulation tools is preferred.

🏝️ Benefits

• Variable pay, provided as a monetary bonus or in another format.

• Medical insurance.

• Dental insurance.

• Vision insurance.

• Flexible spending accounts.

• Health savings accounts.

• Life insurance.

• Accidental Death and Dismemberment (ADD) insurance.

• Disability benefits.

• Retirement benefits.

• Paid vacation/time off.

• Educational assistance.

• Potential inclusion of infertility assistance.

• Potential inclusion of paid parental leave.

• Potential inclusion of adoption assistance.

• Flexible work environment.