DevOps Engineer
Stanford Health Care2 months ago
Newark, CA, USAMid Level
Responsibilities
- Design, build, and maintain scalable cloud-based infrastructure, containerization, and orchestration platforms for AI/ML systems.
- Develop CI/CD pipelines for deployment, testing, and monitoring of AI/ML models and applications.
- Optimize model training, deployment, inference, and LLM pipelines with data scientists, data engineers, and software engineers.
- Monitor and troubleshoot AI/ML systems for availability, performance, reliability, infrastructure utilization, costs, and GPU usage.
- Maintain Kubernetes pods, container registries, virtual machine image libraries, model registries, infrastructure-as-code repositories, and multi-cloud environments.
- Implement security, data privacy, compliance, observability, and safety practices for AI/ML workflows and infrastructure.
- Evaluate and integrate MLOps, DevOps, cloud, and agentic application tools and frameworks.
- Mentor junior team members and provide technical guidance.
Requirements
- Bachelor’s or higher degree in Computer Science, Engineering, or a related field.
- At least three years of directly related experience and proven experience as an MLOps Engineer.
- Strong knowledge of AWS, Azure, or Google Cloud and infrastructure-as-code tools such as Terraform or CloudFormation.
- Proficiency with Docker and Kubernetes.
- Experience with GitLab CI/CD, GitHub Actions, or CircleCI.
- Programming and scripting experience with Python, Rust, or Go.
- Familiarity with PyTorch, TensorFlow, and scikit-learn.
- Understanding of DevOps principles, software development lifecycle practices, and agile methodologies.
- Strong troubleshooting, problem-solving, communication, and cross-functional collaboration skills.
Benefits
- Full-time, 1.0 FTE, day shift with an eight-hour schedule.
- Hybrid work arrangement.
- Stanford Health Care role supporting patient care, medical research, and operational services.
Tech Stack
Categories