Machine Learning Engineer

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 role in shaping the future of manufacturing and mobility. By leveraging data, advanced analytics, AI, and modern engineering practices, we partner with Manufacturing teams to turn complex operational challenges into scalable solutions that improve quality, efficiency, safety, cost, employee experience, and customer value. Join us and apply your AI/ML expertise and analytical skills to help shape the next generation of intelligent vehicles.

In this position...

We are seeking a highly skilled DIA Machine Learning Engineer to design, develop, deploy, and scale AI/ML and advanced analytics products for manufacturing. In this role, you will combine deep technical expertise in machine learning, MLOps, cloud technologies, and data science with strong business acumen to translate complex manufacturing challenges into scalable, production-ready solutions that deliver measurable business value.

Based in Dearborn, MI, this is a hybrid position with a requirement to be onsite four or more days per week. Relocation assistance may be available for qualified candidates.

What you’ll do …

• Design, develop, test, deploy, and maintain scalable machine learning, deep learning, Generative AI, optimization, statistical, and advanced analytics solutions for complex manufacturing challenges.
• Build and productionize end-to-end AI/ML products, including data preparation, feature engineering, model development, validation, deployment, monitoring, and continuous improvement.
• Develop reusable ML frameworks, MLOps pipelines, APIs, and engineering patterns that enable reliable, scalable, and maintainable AI/ML solutions.
• Develop and deploy scalable AI and machine learning solutions on GCP using services such as Vertex AI, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, Pub/Sub, and related data and AI services.
• Establish and monitor model performance, data quality, system reliability, and business-value metrics to ensure deployed solutions deliver sustained impact.
• Proactively identify and mitigate production risks, including model and data drift, data availability, scalability, security, explainability, performance degradation, and operational support requirements.
• Explore and implement agentic AI patterns such as planning, tool and function calling, memory, reflection, human-in-the-loop approvals, and multi-step workflow execution.

Business Engagement & Cross-Functional Collaboration

• Partner directly with Manufacturing teams to understand business processes, identify opportunities, define problem statements, and translate operational needs into actionable analytics and AI products.
• Communicate complex technical concepts, model results, risks, and tradeoffs in clear, practical language for technical and non-technical stakeholders.
• Balance experimentation and innovation with disciplined delivery, ensuring solutions are fit for purpose and aligned to measurable business outcomes.
• Provide technical recommendations that help stakeholders make informed decisions regarding technology selection, solution design, deployment strategies, and future investments.

Innovation, Emerging Technology & Applied Research

• Evaluate emerging AI and manufacturing technologies, including Generative AI, Agentic AI, machine vision, IIoT, digital twins, optimization, and advanced ML, and collaborate with universities, research partners, and the GDI&A AI Advancement Center to translate promising innovations into practical, production-ready solutions.
• Stay current with advancements in AI/ML, cloud, data science, manufacturing analytics, and software engineering, while contributing to reusable assets, engineering standards, technical communities, documentation, and knowledge sharing across GDI&A and Manufacturing Analytics.

We recognize that no one person will embody every single quality or skill listed below. If you are passionate about applying AI, machine learning, data science, and modern engineering practices to transform manufacturing, we encourage you to apply.

Education

• Master’s degree in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Engineering, Operations Research, Industrial Engineering, or a related technical discipline.
• Equivalent combination of advanced education, relevant technical experience, and demonstrated AI/ML expertise may be considered.

You'll have...

• Strong experience applying machine learning, deep learning, computer vision, NLP, Generative AI, and advanced analytics, with proficiency in Python, SQL, and modern ML/DL frameworks to solve real-world problems using large, complex structured and unstructured data.
• Experience designing, developing, and deploying production-grade AI/ML solutions using cloud platforms, preferably Google Cloud Platform (GCP), and MLOps practices including data pipelines, APIs, model deployment and monitoring, containerization, CI/CD, testing, and source control.
• Strong experience translating complex business problems into scalable AI/ML solutions, including data quality assessment, model selection and validation, performance evaluation, technical tradeoffs, and effectively communicating results to technical and business stakeholders.

Even better, you may have...

• Ph.D. in Data Science, Statistics, Economics/Econometrics, Mathematics, Operations Research, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Hands-on experience with Google Cloud Platform (GCP), AI/ML, MLOps, Generative AI, RAG, and Agentic AI/LLMs, including production capabilities such as model deployment, monitoring, governance, and automation.
• Experience applying advanced analytics technologies such as machine vision, sensor and time-series data, IIoT, optimization, simulation, operations research, and digital twins to manufacturing or operational challenges.
• Familiarity with data governance, cybersecurity, privacy, responsible AI, and enterprise architecture, along with experience contributing to reusable solutions, technical standards, knowledge sharing, and collaboration with research or technology partners.

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:

• Immediate medical, dental, and prescription drug coverage
• Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care and more
• Vehicle discount program for employees and family members, and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
• Paid time off and the option to purchase additional vacation time.

For a detailed look at our benefits, click here:Benefit Summary

This position is a salary grade 7 or 8.

This position is a salary grade 7 or 8 and ranges from$99,600-$192,900.

Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.

*Visa Sponsorship is not provided for this role *

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, If you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.