Machine Learning Engineer

Job Description

At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow’s transportation. The future of smart mobility hinges on the intelligent application of data, metrics, and analytics. As part of our Global Data Insight & Analytics (GDI&A) team, you will play a pivotal role by serving as Ford’s trusted adviser, providing clear insights into business conditions, customer needs, and the competitive environment. Your work will empower key decision‑makers to act decisively and positively. You will leverage your expertise in data and analytics to contribute to timely, evidence‑based decision‑making across a range of domains including Connected Vehicle, Smart Mobility, Operations, Manufacturing, Supply Chain, Logistics, and Warranty Analytics.

Responsibilities

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 to present results in a clear and concise manner

Qualifications

Bachelor’s degree in computer science, mathematics, statistics, operations research, or a related field

1+ years of experience in one or more core domains involved in machine‑learning model deployment, including data engineering, model building, MLOps

Experience with the complete software lifecycle

Strong technical writing and oral communication skills

Experience in productionizing generative AI to solve critical business problems

Preferred Qualifications

Master’s degree in computer science, mathematics, statistics, operations research, or a related field

OR bachelor’s degree in computer science, mathematics, statistics, operations research, or a related field AND 2+ years data‑science experience

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, including development and deployment of LLM‑driven AI agents capable of autonomous task execution and tool integration)

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)

Seniority Level

Associate

Employment Type

Full‑time

Job Function

Engineering and Information Technology

Industries

Motor Vehicle Manufacturing

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