Ford
Auto · Automaker
- HQ
- Dearborn, US
- Founded
- 1903
- Size
- 180,000+
- Website
- ford.com
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 Intelligence & Integration, Product Manager Senior Product Manager to lead the strategy and execution of a consumer AI assistant on mobile, focusing on improving customer needs fulfillment and driving adoption/engagement. The role involves defining product vision, roadmap, and growth strategies, partnering with AI/ML and engineering teams to enhance assistant quality, and using data and AI evaluations for prioritization. | Agent | 7 |
| Senior Software Engineer Senior Software Engineer role focused on building and deploying Generative AI, LLM-powered applications, RAG pipelines, and multi-agent systems within an industrial analytics context on Google Cloud Platform (GCP). The role involves full-stack development, cloud infrastructure management with Terraform, and leveraging AI tools for software engineering. | Agent | 7 |
| AI Platform Administrator The AI Platform Administrator is responsible for the operational governance, security, lifecycle management, and enterprise adoption of AI agents and agentic capabilities across the organization. This role serves as a platform lead helping to define strategy for agentic AI solutions across Microsoft Copilot, Google Gemini, Anthropic, and use of LLMs within the enterprise. The position ensures AI solutions are deployed securely, comply with corporate governance requirements, align with enterprise architecture standards, and deliver measurable business value. The AI Administrator works closely with developers, architects, cybersecurity, compliance teams, platform engineers, and business stakeholders to establish a scalable and governed AI ecosystem. | Agent | 7 |
| Autonomous Robotics Launch Manager Lead a multi-plant engineering team to define, develop, and deploy next-generation autonomous robotics technologies for Ford's manufacturing logistics. This role oversees AMR/AGV platforms, embedded controls, ML-based perception, ADAS-inspired autonomy, and large-scale software integrations. Responsibilities include technical leadership for autonomy software, sensor fusion, perception, mapping, localization, motion planning, and safety systems, as well as software-driven project execution and multi-plant launch leadership. The role also involves embedded controls and hardware integration, and software validation using simulation environments. | AgentData | 7 |
| Data Scientist - Conversational AI Data Scientist for Ford's next-generation AI Digital Assistant, focusing on Product Analytics and Applied ML. The role involves NLP for utterance analysis, evaluating AI response quality, data integration on GCP, defining conversational metrics, and building dashboards. The goal is to enhance the driving experience by expanding the AI assistant from mobile to in-vehicle systems. | Agent | 7 |
| Full Stack Software Engineer - AI Applications Full Stack Software Engineer focused on building and orchestrating AI agents and applications within an enterprise context, emphasizing cloud-native development on GCP and integrating various systems. The role involves designing, deploying, and operating AI-powered applications, RAG pipelines, and LLM integrations, with a focus on developer productivity and automation. | Agent | 7 |
| Director, AI Transformation Architect Director-level role focused on identifying, redesigning, and scaling AI-enabled workflows within Ford's Integrated Services organization. The role involves hands-on building and prototyping of AI agents, automation, and infrastructure to improve speed, quality, and decision-making across product management, engineering, and go-to-market functions. It emphasizes responsible AI implementation, governance, and driving adoption through training and best practices. | Agent | 7 |
| Senior Software Engineer — DevOps & Platform, AI Systems Senior Software Engineer focused on building and operating the cloud-native AI platform at Ford, emphasizing automation, agent orchestration for operational tasks, and supporting AI workloads like LLMs and agentic systems. The role involves designing and managing GCP infrastructure, CI/CD pipelines, and ensuring reliability and security for AI systems. | AgentServe | 7 |
| Technical Product Manager Technical Product Manager for Vehicle Electrical Software & Systems Engineering (VESSE) Ecosystem of AI Tools. Leads strategy and adoption of AI solutions to accelerate design, development, and validation of vehicle electrical and software systems. Uses low-code/no-code tools to prototype AI-driven engineering solutions, drives adoption of existing tools, and builds business cases for scaling innovations. Integrates AI tools with VESSE workflows and partners with data engineers for data access. | Agent | 7 |
| Full Stack Software Engineer - AI Applications This role focuses on building and shipping AI-powered applications and agents, specifically RAG pipelines, LLM integrations, and agentic workflows, within an enterprise context. The engineer will orchestrate agents for development, connect disparate systems, and automate manual processes, while also owning the cloud-native infrastructure on GCP and CI/CD pipelines. The emphasis is on practical application and production deployment of AI within a large organization. | Agent | 7 |
| 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 |
| Sr. Specialist, Yield Management - GTM AA Data Scientist This role focuses on developing, deploying, and enhancing machine learning models for yield management and advanced analytics within Ford. The Data Scientist will own the lifecycle of these models, ensuring scalability and robustness, and will translate complex data into actionable business decisions for stakeholders. | Post-train | 7 |
| Data Anchor Ford is seeking an AI/ML Engineer to build and scale data platforms and AI/ML solutions for automotive manufacturing. The role involves architecting and deploying ML models, managing IIoT pipelines, and leveraging Generative AI with tools like Gemini Enterprise on GCP. Responsibilities include data anchoring, cloud infrastructure management, and model monitoring. | ServeData | 7 |
| Sr. Manager, Yield Management - GTM Advanced Analytics Senior Manager to lead the strategic development, deployment, and enhancement of AI/ML solutions for Yield Management at Ford. This role involves leading a team to transform business processes using predictive modeling, forecasting, segmentation, and optimization algorithms, with a focus on delivering end-to-end production-grade AI solutions. Key responsibilities include managing the AI/ML lifecycle, developing demand sensing algorithms, driving innovation with Agentic AI, establishing MLOps and Responsible AI practices, and collaborating with business stakeholders. | AgentData | 7 |
| DAT In-House Perception Algorithm Engineer Develops and integrates ADAS perception algorithms using C++ for embedded systems, applying machine learning and computer vision techniques to ADAS solutions with sensors like LiDAR, Radar, USS, and Camera. Requires experience in ADAS vehicle testing, data processing, validation, MISRA C++ coding standards, CI/CD pipelines, Git, and Agile methodologies. | Agent | 7 |
| Product Manager & Data Science Supervisor This role supervises a global cross-functional team of data scientists, analysts, engineers, and designers to deliver analytics-driven solutions and product initiatives. The responsibilities include identifying opportunities for process optimization via data-driven approaches, organizing large datasets, applying data mining and machine learning models, creating visualizations, and working with IT to implement analytics tools. The role involves developing analytic models, supporting Reductive Design decisions, formulating problems, translating business requirements into analytical projects, and communicating findings to various stakeholders. It also includes project ownership, planning, tracking, and building advanced analytics models in the supply chain space, with a specific requirement for developing, fine-tuning, and deploying LLMs for NLP tasks. | AgentData | 7 |
| Software Engineer, AI Enablement Software Engineer to design and build AI-powered agents for intelligent discovery, recommendation, and management of enterprise ontology assets, requiring strong software engineering skills and practical AI experience in information discovery, recommendation, and search. | Agent | 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 |
| Principal AI/ML Engineer (Cybersecurity & AIOps) Principal AI/ML Engineer focused on cybersecurity and AIOps, leading the design, development, and deployment of AI/ML solutions. This role involves building and operationalizing models for anomaly detection, predictive analytics, and classification, with a strong emphasis on Generative AI and Agentic AI for automation and threat intelligence. The engineer will architect ML pipelines, work hands-on with data, and translate technical outcomes for stakeholders, bridging data science with security operations. | AgentServe | 7 |