Advise and leads development of tooling for AI/ML development and deployment.
Lead deployment and maintenance of infrastructure, model monitoring and observability tools, providing an effective model development platform for data scientists and ML engineers.
Collaborate with machine learning model developers to bring ML models to production.
Mentor and leads a team of engineers focused on deploying machine learning pipelines at scale.
Partner with product, architecture, and other engineering teams to define scalable and performant technical solutions.
Influence across business, product, and technology teams and successfully manages senior stakeholder relationships
Champion the firm’s culture of diversity, equity, inclusion, and respect.
Required qualifications, capabilities and skills
Formal training or certification on software engineering concepts and MLOps applied experience.
Experience with machine learning engineering and operations in a large enterprise.
Experience in building, evaluating and deploying ML models into production
Experience leading complex projects supporting system design, testing and operational stability.
Demonstrated prior experience influencing across complex organizations and delivering value at scale.
Extensive practical cloud native experience
Proven expertise on adoption of agile practices to deliver efficiently and to the expected quality solutions.