Research ML Ops Software Engineer

Siemens Healthineers • Knoxville, TN

84d • $97,100 - $145,600

About The Position

Join us in pioneering breakthroughs in healthcare. For everyone. Everywhere. Sustainably. Our inspiring and caring environment forms a global community that celebrates diversity and individuality. We encourage you to step beyond your comfort zone, offering resources and flexibility to foster your professional and personal growth, all while valuing your unique contributions. As a Research ML Ops Software Engineer, you will build and maintain infrastructure to support the end-to-end lifecycle of machine learning experiments from data ingestion and training to deployment, monitoring, and compliance. You will collaborate with research scientists, data engineers, and software developers to ensure reproducibility, scalability, and regulatory traceability across AI workflows for medical devices. Apply now for the position of Research ML Ops Software Engineer to join our research team focused on developing and deploying cutting-edge machine learning models.

Requirements

• Bachelor's or M.S. in Computer Science, Software Engineering or related field.
• Minimum of 3 years of experience (advanced degree may be substituted for experience, where applicable) in MLOps, DevOps or data engineering roles.
• Experience with cloud platforms and local/on-prem computer clusters.
• Programming skills in C / C++ and at least one other language (preferably Python), and knowledge of industrial approaches of software development.
• Familiarity with medical imaging would be beneficial (SPECT, PET, CT, DICOM, coordinate systems, image registration, etc.).
• Familiarity with deep learning libraries.
• Knowledge of regulatory requirements for AI medical devices will be beneficial.
• Familiarity with different types of databases.

Responsibilities

• Designing and implementing scalable, reproducible ML pipelines for research workflows.
• Automating data versioning, model tracking, and artifact management.
• Containerizing training and inference environments.
• Integrating model lineage tracking with research databases.
• Collaborating with data scientists to transition research code into production-ready workflows.
• Ensuring infrastructure supports compliance, audit logging, and regulatory reporting (e.g., 21 CFR Part 11).
• Supporting Continuous Integration (CI)/ Continuous Deployment (CD) workflows for experiments and reproducible reporting.
• Developing monitoring tools for model drift, data quality, and performance metrics.
• Collaborating across teams to promote best practices in experiment reproducibility, documentation, and governance.

Benefits

• medical insurance
• dental insurance
• vision insurance
• 401(k) retirement plan
• life insurance
• long-term and short-term disability insurance
• paid parking/public transportation
• paid time off
• paid sick and safe time

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Computer and Electronic Product Manufacturing
• Education Level: Bachelor's degree