ML Enablement Engineering Manager 

Position Overview 

As the Machine Learning Enablement Engineering Manager within Ford’s Data Platforms and Engineering (DP&E) organization, you are a key leader responsible for guiding and developing a team of engineers focused on delivering high-impact, scalable machine learning solutions to address critical business challenges within DP&E. Your primary focus will be on building and maintaining the platform infrastructure and processes that empower data scientists and ML engineers to rapidly deploy and scale their solutions into production. You will work closely with Product Managers, Architects, Data Scientists, and other key stakeholders to drive engineering excellence, promote innovation, and uphold best practices. This role is less about building individual ML models and more about creating robust, reliable, and scalable solutions that allow others to deliver value effectively. 

Your leadership is crucial in driving the success of our machine learning initiatives. Your ability to guide and develop a team of engineers, while maintaining alignment with Ford’s strategic goals, will be key to delivering world-class, production-ready ML solutions that power Ford’s transformation into a data-driven enterprise. 

You should be a highly hands-on engineering leader with a proven track record of delivering complex, scalable solutions. While a deep understanding of ML concepts is beneficial, your primary focus will be on platform engineering, DevOps, and building robust, maintainable infrastructure. You will define processes for technical platforms, conceive application prototypes, and mentor your team in best practices. Your day-to-day responsibilities will involve designing and managing the organization's ML infrastructure architecture, ensuring data is efficiently processed, stored, and accessed to support ML model development and deployment. You will be pivotal in delivering these solutions on time and within budget.