ML Ops Manager

Company Description

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com

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.

Qualifications

• 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.

• Deep expertise in on-prem containerization and orchestration (e.g., Docker, Podman, Kubernetes, OpenShift, Rancher).

• Strong experience with Infrastructure as Code (e.g., Ansible, Puppet, Terraform (private cloud)).

• Proficient in automation and scripting using Python, Bash, or similar tools.

• Solid grasp of MLOps best practices, including CI/CD, model monitoring, and compliance.

• Hands-on experience with version control and CI/CD tools (e.g., Git, GitHub/GitLab, Jenkins, GitLab CI, GitHub Actions).

• Excellent leadership, project management, and stakeholder communication skills.

• Ability to drive a culture of continuous improvement, innovation, and collaboration.