Ford currently has 28 active AI-related job listings. The majority of these roles, 50%, are focused on agents, with application roles making up another 21%. Engineering is the most frequent function hiring for these positions. Recent hiring trends show a decrease, with 23 new AI roles posted in the last 30 days, a 42% reduction compared to the preceding 30-day period.
Currently tracking 18 active AI roles, with 460 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$268k (avg $158k).
Ford currently has 28 active AI-related roles in our index. The most common open titles are: Full Stack Software Engineer - AI Applications (2), AI Platform Administrator, Autonomous Robotics Launch Manager, Chief Engineer, AI Product Creation, DAT In-House Perception Algorithm Engineer. Most positions are in Engineering and Product.
Ford's active AI hiring is concentrated in: agents (57%), application (18%), serving infrastructure (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Ford is hiring AI talent in: United States (28 roles).
Job postings at Ford most frequently mention: Statistics, Python, Predictive Modeling, Machine Learning, GCP.
In the past 30 days, Ford has posted 22 new AI-related roles. That is a -41% change versus the prior 30 days (37 → 22).
| Title | Stage | AI score |
|---|---|---|
| Vehicle Prognostics - Applied Data Scientist Applied Data Scientist at Ford focused on developing and deploying prognostic features for vehicle components, using Physics-Informed Machine Learning, C++ edge model deployment, and end-to-end pipeline ownership from simulation to production. The role involves analyzing high-frequency signal processing, multi-sensor fault detection, causal inference, and big data ingestion. | ShipAgent | 7 |
| Chief Engineer, AI Product Creation Lead the strategic integration of AI and digital technologies into Ford's Global Product Development System (GPDS) to optimize engineering workflows, accelerate development cycles, and drive product excellence. This role involves architecting AI integration across the product creation lifecycle, recommending investments, designing systems for workflow optimization, leveraging historical data, enhancing virtual validation, and leading global cross-functional efforts to modernize systems and deploy next-generation tools. The focus is on tactical efficiency, system integration, and establishing a digital-first development cycle. | ShipAgent | 7 |