Project Manager, MLOps

[Project Leadership]

• Define and execute the roadmap for MLOps edge and cloud infrastructure transformation.
• Coordinate cross-functional teams, monitor project performance, and report progress including risks and mitigations.
• Manage overall AI projects (planning, execution, and monitoring), including tracking project milestones and deliverables toward timely completion.
• Champion Agile, Scrum, or hybrid methodologies as appropriate.

[Technical AI and MLOps]

• Lead medium-scale migrations, ensuring seamless transitions with minimal disruption while optimizing performance, security, and cost.
• Implement and facilitate data preparation and placement strategies to optimize data usability.
• Lead a team of data scientists on future AI and MLOps strategies, including focus on an AI/MLOps Hub for agentic agents, model metrics, and data integrity.
• Establish and refine MLOps best practices, tools, and frameworks to enhance developer experience, agility, and efficiency.
• Drive continuous improvements in MLOps edge/cloud performance, scalability, optimization, and robust system testing delivery.
• Manage relationships with key technology vendors, negotiate contracts, and ensure optimal utilization and cost efficiency.
• Review industry trends with continuous evaluation of cutting-edge technologies to improve developer reliability and efficiency.
• Demonstrate experience in leading enterprise-scale edge and MLOps transformations (regionally/globally) for ML models and pipelines to the cloud.
• Develop and enforce best practices for infrastructure, application deployment, and operations within the IoT Platform.
• Develop your team by coaching, facilitating career progression, and providing growth opportunities.
• Regularly communicate with team members, provide performance feedback, and conduct evaluations.
• Build collaborative partnerships with Software Architects, Technical Leads, Product Owners, Product Managers, Data Scientists, Data Engineers, and Software Developers.

[Technical Leadership & Collaboration]

• Prepare reports on project progress, challenges, and achievements.
• Collaborate closely with IoT/PLC engineers and domain experts.
• Present findings to stakeholders and senior management.
• Contribute to and maintain comprehensive documentation, design decisions, and technical standards via playbooks.
• Mentor junior engineers through training and support team members on AI and ML tools and techniques.
• Develop training materials and conduct workshops as needed to enhance cross-functional team capabilities.