Senior MLOps Engineer

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Requirements:

• 4+ years of relevant hands-on experience.
• 3+ years' experience with Docker and Kubernetes, provisioning production clusters, and maintaining compliance.
• 3+ years experience supporting enterprise Cloud applications or infrastructure (AWS, Azure, etc.).
• Solid understanding of Helm Charts, practical experience with Machine Learning on Kubernetes, and experience managing GPU clusters.
• Practical programming and scripting skills (Python preferred) and proven experience with modern software development practices.

Responsibilities:

• Support the development of a real-time data platform for the Department of Defense (DoD).
• Aggregate real-time data from over 750 sensors and process over a billion events daily.
• Your primary responsibilities will include deploying ML infrastructure, building MLOps pipelines, and contributing to the full lifecycle of the ML platform.