Machine Learning Operations Engineer (MLOps)

Role overview

As a Machine Learning Operations (MLOps) Engineer in Bellevue, WA, you’ll join a new team within SAP’s AI & Support Engineering organization. The team builds and maintains AI/agentic solutions used in SAP’s customer support ecosystem, collaborating with thousands of support engineers worldwide.

What you’ll do

• Build and maintain AI infrastructure and pipelines for training, evaluation, deployment, and monitoring.
• Design CI/CD workflows for the full ML lifecycle (model training → evaluation → deployment → monitoring).
• Automate model versioning, experiment tracking, and reproducibility.
• Operationalize and serve models reliably in collaboration with engineering teams.
• Manage the AI infrastructure stack, including GPU resources, orchestration, and serving frameworks.
• Optimize cost and resource utilization.
• Work with security engineers to meet enterprise security, compliance, and availability requirements.
• Establish and improve MLOps best practices.
• Report progress to leadership.

What you bring

• 3+ years of experience in MLOps, DevOps, or platform engineering for ML/AI systems.
• Proficiency with containerization and orchestration: Docker and Kubernetes.
• Experience with ML lifecycle tooling such as MLflow and/or Kubeflow.
• Hands-on cloud + infrastructure-as-code: Azure and Terraform.
• Familiarity with LLM serving, inference optimization, and model-serving frameworks.
• Strong software engineering and scripting, especially Python.
• Experience with monitoring, observability, and alerting for production systems.
• Experience building automated, reliable CI/CD pipelines.
• Knowledge of security and compliance requirements for enterprise software.

Nice-to-haves

• Passion for AI and automation; ability to work in a collaborative, mission-critical environment.

Location

• Bellevue, WA