Job
Description
We are looking for an experienced MLOps Manager with a proven track record of leading teams in designing, building, and managing machine learning infrastructure and pipelines in on-premises environments. The ideal candidate will bring 9+ years of experience in DevOps / MLOps, including hands-on leadership in delivering multiple end-to-end MLOps projects. You will oversee the MLOps function, enabling scalable, secure, and efficient ML operations, while collaborating closely with Data Science, IT, and Engineering teams. Key Responsibilities Lead the design, development, and management of robust ML pipelines and infrastructure in on-premises or private cloud environments. Define and drive MLOps strategy and best practices for model deployment, monitoring, and lifecycle management. Oversee the implementation and governance of Infrastructure as Code (IaC) using tools like Ansible, Terraform (for private cloud), or Puppet. Manage, mentor, and guide MLOps engineers, fostering a high-performing and collaborative team. Collaborate with cross-functional teams to align MLOps solutions with business and data science objectives. Drive automation and standardization of CI/CD pipelines, model versioning, and container orchestration (e.g., Docker, Kubernetes, OpenShift). Ensure comprehensive documentation of infrastructure, architecture, and operational workflows using tools like Confluence, GitHub Wikis, and system diagrams. Identify and implement optimization opportunities for ML infrastructure performance, cost, and scalability. Stay updated on industry trends and emerging technologies to continuously enhance MLOps capabilities. 9+ years of experience in DevOps / MLOps with at least 4 years in a leadership or managerial role. Demonstrated success in delivering multiple MLOps projects in on-premises or private cloud environments.
