Senior AI Platform & MLOps Engineer

Stanford Health Care; Town of Newark (WI); On-site; USD 165,000 - 218,000; Full time

Job summary

Stanford Health Care seeks a Senior AI Platform & ML Ops Engineer to architect the layered infrastructure for autonomous, agentic systems across the organization. The role combines expert-level DevOps with agentic application development to build a robust AI factory that interacts with healthcare APIs and enforces ML Ops observability and safety guardrails.

The engineer will design cloud-based infrastructure as code, deploy scalable microservices, and lead cross-functional collaboration with

Qualifications

• Bachelor’s or higher degree in Computer Science, Engineering or a related field.
• Three (3) or more years of directly related experience.

Responsibilities

• Design, build and maintain scalable and robust infrastructure for AI/ML systems, including cloud-based environments, containerization and orchestration platforms.
• Develop and implement CI/CD pipelines to automate the deployment, testing and monitoring of AI/ML models and applications.
• Collaborate with data scientists, data engineers and software engineers to optimize model training, deployment and inference pipelines.
• Monitor and troubleshoot AI/ML systems to ensure high availability, performance and reliability.
• Maintain and monitor model training and inference pipelines across multi-cloud tenants especially around Large Language Models (LLMs).
• Maintain Kubernetes pods, container registry and virtual machine image library and model registry
• Monitor infrastructure utilization and costs pertaining to model training, inference and GPU utilization
• Implement best practices for security, data privacy and compliance in AI/ML workflows and infrastructure.
• Evaluate and integrate new tools, technologies and frameworks to improve the efficiency and effectiveness of our MLOps processes.
• Mentor and provide technical guidance to junior members of the organization.
• Stay up-to-date with the latest advancements and trends in MLOps, DevOps and cloud technologies and share them with the team.

Skills

Kubernetes

Terraform

Python

Docker

Go

Rust

CI/CD

LangGraph

CrewAI

Tool calls

PyTorch

TensorFlow

Scikit-learn

DevOps

Education

Bachelor’s degree

Tools

CloudFormation

Job description

Stanford Health Care seeks a Senior AI Platform & ML Ops Engineer to architect the layered infrastructure for autonomous, agentic systems across the organization. The role combines expert-level DevOps with agentic application development to build a robust AI factory that interacts with healthcare APIs and enforces ML Ops observability and safety guardrails.

The engineer will design cloud-based infrastructure as code, deploy scalable microservices, and lead cross-functional collaboration with