We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world - together. At Ford, we’re all a part of something bigger than ourselves. Are you ready to change the way the world moves?
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…

The Global Data Insight & Analytics organization is seeking a Software Engineer to lead and advance our internal Data Science and AI/ML strategy. In this role, you will be part of a dynamic, cross-functional team, collaborating closely and consistently with other engineers, business partners, product managers, and designers. You will be involved in frequent and iterative releases. Your focus will be on backend software engineering, specifically in developing machine learning and generative AI applications on Google Cloud, as well as creating reusable AI/ML components.

• Work closely with Tech Anchor, Product Manager and Product Owner to deliver Gen AI solution in GCP using Python and other tools for business across the company.
• Work with software and ML engineers/Data Scientist to tackle challenging AIOps and Gen AI problems.
• Develop and manage current CI/CD ecosystem and tools
• Find ways to automate and continually improve current CI/CD processes and release processes
• Help innovate standardize machine learning development practices.
• Experiment, innovate and share knowledge with the team.
• Lead by example in use of Paired Programming for cross training/upskilling, problem solving, and speed to delivery.
• Work with other software engineers to cooperatively deliver user stories, as well as solve highly complex technical software problems using industry best practices
• Leverage latest ML/Gen AI / GCP/AIOPs/Kubernetes technologies