MLOps Engineer

A Brief Overview Senior AI Platform & ML Ops Engineer responsible for building and maintaining scalable, robust infrastructure for AI/ML systems in Stanford Healthcare. Tasks include designing cloud-based environments, containerization, orchestrating multi-agent frameworks, and ensuring observability, safety, and compliance. Locations Stanford Health Care What you will do 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. Education Qualifications Bachelor’s or higher degree in Computer Science, Engineering or a related field. Experience Qualifications Three (3) or more years of directly related experience. Required Knowledge, Skills and Abilities Proven experience as an MLOps Engineer. Strong knowledge of cloud platforms such as AWS, Azure or Google Cloud and experience with infrastructure-as-code tools like Terraform or CloudFormation. Proficiency in containerization technologies such as Docker and container orchestration platforms like Kubernetes. Experience with CI/CD tools such as GitLab CI/CD, Github Actions or CircleCI. Solid programming skills in languages such as Python, Rust or Go and experience in scripting and automation. Familiarity with machine learning frameworks and libraries such as PyTorch, Tensorflow and scikit-learn. Deep understanding of DevOps principles, agile methodologies and software development lifecycle. Strong problem-solving and troubleshooting skills, with the ability to analyze and resolve complex technical issues. Excellent communication and collaboration skills with the ability to work effectively in cross-functional teams. Physical Demands and Work Conditions Category III – Tasks that involve no exposure to blood, body fluids or tissues. Equal Opportunity Employer Stanford Health Care (SHC) strongly values diversity and is committed to equal opportunity and non-discrimination in all its policies and practices, including the area of employment. Accordingly, SHC does not discriminate against any person on the basis of race, color, sex, sexual orientation or gender identity and/or expression, religion, age, national or ethnic origin, political beliefs, marital status, medical condition, genetic information, veteran status, or disability. People of all genders, all racial and ethnic groups, people with disabilities, and veterans are encouraged to apply. Qualified applicants with criminal convictions will be considered after an individualized assessment of the conviction and the job requirements. Base Pay Scale Generally starting at $79.21 - $104.97 per hour. The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, specialty and training. This pay scale is not a promise of a particular wage. #J-18808-Ljbffr