Machine Learning Engineer

Ford • Dearborn, MI

13h • $74,300 - $144,900 • Hybrid

About The Position

Ford’s Global Data Insight & Analytics (GDI&A) department uses data, analytics, and modeling to support evidence-based decision-making across domains including connected vehicles, smart mobility, operations, manufacturing, supply chain, logistics, and warranty analytics. The Machine Learning Engineer applies AI and machine learning to real-world challenges and helps innovate in areas such as autonomous vehicles, cybersecurity, customer interaction, and product design.

The role spans project stages from identifying problems through deploying models. The engineer analyzes structured and unstructured data, develops insights from high-volume and high-dimensional data, and communicates analytical results and models to business partners and executive management. The position offers opportunities to conduct original research, choose suitable methodologies, and contribute to machine learning solutions that shape Ford’s strategic direction.

Requirements

• Master’s degree in Computer Science, Mathematics, Statistics, Operations Research, or a related field and at least 1 year of Data Science experience; or a bachelor’s degree in one of these fields and at least 2 years of Data Science experience.
• At least 1 year of experience delivering and maintaining production software products.
• Experience with cloud-based deployments and best practices.
• Demonstrated contributions and expertise in at least one AI domain: Natural Language Processing, Computer Vision, Generative AI, or physics-informed neural networks.
• For Natural Language Processing: experience with LLM fine-tuning and distillation, evaluating LLM-powered applications, or deploying models at scale.
• For Computer Vision: experience with anomaly detection or few-shot learning, multi-sensor fusion, object detection and tracking, scene segmentation, or motion planning and prediction.
• For Generative AI: experience fine-tuning Stable Diffusion models, multimodal large language models, or generation in the 3D domain.
• For physics-informed neural networks: experience with machine learning for computational fluid dynamics or finite element analysis, point-cloud or mesh-based neural networks, or PDE surrogate modeling.
• Must be legally authorized to work in the United States; employment eligibility will be verified at hire.

Responsibilities

• Analyze source data and data flows, including structured and unstructured text, audio, images, and video.
• Manipulate high-volume, high-dimensional data from different sources to identify patterns, anomalies, relationships, and trends.
• Apply AI and machine learning to solve complex, real-world problems.
• Analyze and visualize diverse data sources, interpret results in a business context, and report findings clearly and concisely.
• Fulfill problem-formulation and machine-learning-technique consulting requests in a timely manner.
• Communicate and present analytical models to business customers and executive management.
• Collaborate with business partners and present results clearly and concisely.
• Participate in project stages from problem identification through model deployment.

Benefits

• Immediate medical, dental, vision, and prescription drug coverage.
• Paid parental leave, new parent ramp-up programs, and subsidized backup childcare.
• Family-building benefits, including adoption and surrogacy expense reimbursement and fertility treatments.
• Employee and family vehicle discount program and management leases.
• Tuition assistance.
• Employee resource groups.
• Paid time off for individual and team community service.
• Vacation time, sick/personal time, and paid holidays, including the period between Christmas Eve and New Year’s Day.
• Domestic relocation is available.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level