Machine Learning Engineer

At Ford, you can build more than vehicles. Come build what matters.

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.

Join our Global Data Insight & Analytics team and use your data expertise and analytical skills to drive evidence-based, timely decision making. Our projects span various domains, including Connected Vehicle, Smart Mobility, Operations, Manufacturing, Supply Chain, Logistics, and Warranty Analytics.

As a Machine Learning Engineer, you will:

• Analyze source data and data flows, working with structured and unstructured data (text, audio, images, video, etc.)
• Manipulate high-volume, high-dimensionality data from varying sources to expose and highlight patterns, anomalies, relationships, and trends
• Apply AI and Machine Learning technology to solve complex, real-world problems
• Analyze and visualize diverse sources of data, interpret results in a business context and report results clearly and concisely
• Fulfill problem formulation and ML technique consulting requests in a timely manner
• Communicate and present analytical models to business customers and executive management
• Work collaboratively with different business partners and be able to present results in a clear and concise manner

Qualifications:

• Master's Degree in Computer Science, Mathematics, Statistics, Operations Research, or related field AND 1+ year Data Science experience
• OR Bachelor's Degree in Computer Science, Mathematics, Statistics, Operations Research, or related field AND 2+ years' Data Science experience
• 1+ years' experience with delivering and maintaining production software products
• Experience with cloud-based deployments and best practices
• Demonstrated contributions and expertise in one or more of the following AI domains:
• Natural Language Processing (finetuning and distillation of LLMs, evaluation of LLM-powered applications, deploying models at scale)
• Computer Vision (anomaly detection / few-shot learning, multi-sensor fusion, object detection and tracking, scene segmentation, motion planning and prediction)
• Generative AI (fine tuning stable diffusion models, multi-modal large language models, generation in the 3D domain)
• Physics-informed neural networks (ML for computational fluid dynamics or finite element analysis, point cloud or mesh-based neural networks, PDE surrogate modelling)

Benefits:

• Immediate medical, dental, vision, and prescription drug coverage
• Paid parental leave, new parent ramp-up programs, subsidized back-up childcare and more
• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments 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
• Generous vacation time, sick/personal time, and paid holidays, including between Christmas Eve and New Year's Day

Salary: $74,300-$144,900