Applied AI/ML Software Engineer-Supply Chain AI and Decision Intelligence

We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.

Enterprise Technology plays a critical part in shaping the future of mobility. If you’re looking for the chance to leverage advanced technology to redefine the transportation landscape, enhance the customer experience and improve people’s lives, this is the opportunity for you. Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are.

In this position...

As an Applied AI/ML Engineer in the Supply Chain AI and Decision Intelligence space, you will be the driving force for delivering Ford’s "AI-First" supply chain transformation. This role is focused on the applied implementation of AI: you will develop and deliver the integration of high-performance models (internal or external, e.g., from COTS products) onto Enterprise Knowledge Graphs to solve complex supply chain problems. Central to this role is the adoption of an AI-Driven Software Development Life Cycle (SDLC) leveraging agentic workflows, AI-assisted coding, and automated testing to deliver robust solutions at industrial speed. You will bridge the gap between abstract business problems and scalable technical execution. You aren’t just building chatbots. You are building the intelligence behind a global supply chain, helping the business manage risk, build resilience, and keep factories running. 

This role demands a blend of technical expertise in AI/ML, advanced analytics and data platform engineering, functional expertise in supply chain, and strong technical leadership to influence stakeholders and deliver transformative results. with a particular focus on establishing and standardizing the AI-based SDLC across cross-functional teams.

Based in Dearborn, MI, this is a hybrid position with a required four-day onsite presence each week  Relocation assistance may be available for qualified candidates.