Ford

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Manufacturing Engineer specializing in Vision Systems for a new automotive battery plant. The role involves programming, troubleshooting, and ensuring the performance of industrial vision systems and other automation equipment within a manufacturing environment. While AI/ML is mentioned as a desirable knowledge area, the core responsibilities focus on established manufacturing engineering tasks and controls.

This role is for a Product Development Engineer focused on Exterior Lighting Vision Systems at Ford. The engineer will be responsible for the design ownership of lighting systems, transitioning to Build-to-Print models and utilizing AI-driven engineering. Key responsibilities include developing internal CAD, optical models, and technical data packages, leveraging AI for generative design to optimize performance, and defining technical standards. The role also involves quality engineering, risk mitigation (FMA/FMEA), root cause analysis, and financial/program integrity through Team Value Management and cross-functional integration. The engineer will collaborate with teams, perform technical analyses, lead design reviews, develop system documents, and address issues through root cause analysis.

Lead a team of data scientists responsible for developing, deploying, and improving customer propensity, predictive, prescriptive, and Customer Lifetime Value (CLV) models to enable personalized marketing and better understand customer value. This role will lead the development of Ford's enterprise CLV framework and partner with stakeholders across various departments to integrate modeling outputs into business processes. The role requires strong data science expertise, leadership skills, and the ability to translate technical work into business value.

The Quality Analyst role at Ford Racing focuses on analyzing warranty and connected vehicle data to identify emerging issues and provide insights for problem-solving. This role involves developing data solutions, supporting quality assessments, and leading quality improvement projects using methodologies like Six Sigma and 8D. The position requires experience in Big Data Analytics and quality/product development, with a focus on improving product quality and reducing warranty costs.

This role focuses on functional safety verification and validation (V&V) for embedded automotive software, with a specific emphasis on leveraging AI tools and software to enhance safety processes and develop AI-enhanced tracking and analytic tools for safety dashboards. The candidate will contribute to developing comprehensive safety cases, identifying process gaps, and driving continuous improvement in functional safety.

This role focuses on applying AI, LLMs, and Generative AI within Ford's manufacturing and powertrain engineering operations to enhance efficiency, quality, and decision-making. The engineer will develop and integrate AI solutions into existing digital manufacturing ecosystems, focusing on areas like automated workflows, data analytics, and intelligent automation. The position requires experience in software engineering, AI/ML model building or deployment, and cloud/DevOps practices.

This Principal Cloud Database Engineer role focuses on designing, engineering, and innovating enterprise-scale database platforms on GCP, with a significant emphasis on integrating AI/ML capabilities into database operations and data platforms. The role involves leading modernization efforts, implementing AI-driven automation, and consulting on data pipelines for AI/ML workloads.

This role supports a team of privacy lawyers by managing global legal projects, driving efficiency through technology and AI tools, advising on knowledge management, and conducting research. It requires experience in data privacy, AI, compliance, or legal operations, with a track record of implementing legal technology and AI-driven tools to modernize workflows. Familiarity with AI and LLMs is necessary.

This role focuses on data analytics engineering for global total cost and TVM (Total Value Management) at Ford. The engineer will develop processes, tools, and data using Design Thinking, Lean Design, and Qilksense to support cost reduction activities. They will provide business insights using AI/LLM tools, perform complex data analysis, and develop interactive dashboards using Qliksense and Power BI. The role also involves KPI development, reporting, and program management for cost reduction actions.

Ford Racing is seeking an engineering leader to manage simulation, tools, and methods, with a focus on integrating next-generation analytical, AI, and tire modeling tools. The role involves leading a team, overseeing simulator operations and budgets, and driving the adoption of common tools and methods across racing programs and product development. A key responsibility is the strategic implementation and future growth of AI-based tools to enhance vehicle development and simulator fidelity.

Software Product Engineer to own the end-to-end engineering lifecycle of conversational, voice-forward AI assistant features on the vehicle, from design through production release. This role involves deep technical expertise, product ownership, and engineering execution, partnering with various teams to deliver production quality features impacting millions of customers.

This role involves designing and implementing AI-powered vision control systems for manufacturing, focusing on quality control and process improvement. The specialist will work with various vision cameras, programming software, and automation systems, including PLCs, robots, and CNCs. Responsibilities include troubleshooting, maintaining equipment, and ensuring systems meet specifications and safety standards. The role also involves integrating AI vision systems into existing manufacturing lines and training personnel.

Director of Data Engineering and Architecture at Ford, focused on establishing AI Readiness by defining enterprise standards for AI-ready data, driving platform evolution, and designing data foundations for AI agents and RAG applications. This role requires leadership in data ingestion, transformation, representation, and ensuring scalability, cost-efficiency, and compliance within a GCP environment.

Solutions Engineer to design, deliver, and manage enterprise-grade solutions across the Atlassian ecosystem and adjacent lifecycle tooling. This role will involve configuring Atlassian tools, developing integrations, and launching AI-powered workflows with practical governance and guardrails.

This role is for a Director of Global IT Audit at Ford, focusing on auditing technology risks across various domains including AI, Connected Vehicle, and SaaS implementations. The position involves risk assessment, developing audit plans, and collaborating with various teams to ensure compliance and identify key risk areas, particularly in the context of evolving technologies like AI.

This role is for an IVI Hardware Architecture Technical Specialist at Ford, focusing on the hardware architecture, technical direction, and engineering maturity of in-vehicle infotainment electronic control units. The specialist will define and govern hardware requirements, architecture decisions, design reviews, and validation expectations, ensuring robust, manufacturable designs ready for production. Responsibilities include leading technical reviews, evaluating hardware capability, providing expert guidance, and leading root-cause investigations for complex hardware issues. The role requires extensive experience in automotive electronic hardware design and architecture.

Production Supervisor for a battery pack assembly line at Ford's new BlueOval Battery Park. The role involves leading an hourly team, ensuring safety, driving operational excellence, problem-solving, team development, data-driven decision making, continuous improvement, and collaboration within a manufacturing environment.

This role leads the end-to-end integration of legacy systems with SAP platforms across global manufacturing plants, focusing on defining and governing standard integration templates and ensuring stable, secure, and scalable interfaces. It involves technical integration leadership, project management, and stakeholder coordination.

This role focuses on applying Lean manufacturing principles, specifically Value Stream Mapping (VSM), to identify waste and improve process flow in Ford's manufacturing plants. The specialist will conduct VSM events, facilitate kaizen workshops, analyze process data, and support continuous improvement initiatives. The role requires a Bachelor's degree in a technical field, foundational experience in VSM, and 3 years in a manufacturing environment.

Staff Systems Integration Engineer responsible for end-to-end integration, validation, and release readiness of IVI software across embedded platforms, middleware, multimedia, connectivity, and customer-facing applications. This role involves partnering with system engineers and development teams, developing automated test coverage, designing and maintaining test infrastructure, and diagnosing complex issues across software, hardware, and vehicle networks. Experience with automotive infotainment systems and HIL testing is a plus.

Senior Software Engineer role focused on designing, developing, and maintaining mission-critical cloud platform components for Ford's connected vehicle capabilities. The role involves end-to-end delivery of software services, owning platform infrastructure, acting as a domain owner, and providing technical leadership and architectural guidance for complex distributed systems. Emphasis on full-stack expertise, cloud & DevOps proficiency, quality & performance, operational excellence, and enterprise thinking.

This role focuses on supply chain constraint management within the automotive industry, involving analysis, mitigation strategies, and collaboration with cross-functional teams to ensure production targets and timelines are met. It requires expertise in specific systems like SAC, Pega, and Ascent, and involves monitoring performance metrics and identifying supplier capacity risks.

Lead a team of Feature Systems Engineers within the Enclosures domain, driving the technical strategy, execution, and talent development needed to deliver next-generation Power Enclosure systems from concept through production. This role combines strong technical ownership of the Enclosures feature domain with people leadership responsibility.

Manager for Embedded Software Verification & Validation (V&V) at Ford Model E, focusing on leading a team, defining V&V strategies for embedded software, overseeing automated test frameworks, ensuring quality assurance, and collaborating with cross-functional teams. Requires experience in embedded software V&V, leadership, and knowledge of automotive standards like ISO 26262.

Full Stack Software Development Engineer with 2-3 years of experience to design, build, and scale cloud platforms and APIs for connected vehicle experiences. Responsibilities include developing microservices, deploying on GCP, integrating with mobile and vehicle teams, maintaining CI/CD pipelines, ensuring code quality and security, and implementing observability. Requires experience with Spring Boot/Ktor, GCP, Docker/Kubernetes, CI/CD tools, TDD, and monitoring tools.

Software Engineering Manager at Ford responsible for aligning global technology strategy with regional market needs, leading software engineering teams, driving technology modernization, improving software quality and operational excellence, and partnering with stakeholders to deliver innovative solutions. Focuses on engineering leadership, software delivery, platform modernization, quality, security, technical governance, and organizational transformation.

This role focuses on leveraging connected vehicle data and advanced analytics to identify and resolve Diagnostic Trouble Codes (DTCs) during new vehicle launches. The engineer will lead cross-functional teams to ensure the quality of vehicle subsystems like Infotainment, Body Control Modules, and ADAS, driving initiatives to reduce costs and improve the customer experience. The position involves extracting and analyzing data, leading investigations, managing quality issues, and driving the development of automated detection tools and dashboards.

Develop and integrate innovative, next-generation electrified powertrain systems and technologies for future products, with an emphasis on groundbreaking electrified vehicles. This role involves clean-sheet system architecture, subsystem sizing & selection, prototype integration & commissioning, cross-functional leadership, trade-off analysis, hands-on testing & troubleshooting, data-driven design, systems engineering rigor, and technical reviews.

This role serves as a global authority for Assembly manufacturing processes within Supplier Technical Assistance at Ford. The primary responsibilities include standardizing technical competency, driving excellence across the supply chain, leading the industrialization of new technologies, and developing/delivering technical training for assembly standards. The role involves conducting manufacturing process assessments, problem-solving quality issues, and providing design for manufacturing input. It requires a strong background in assembly processes and craftsmanship, with significant global travel.

Product Development Engineer for intelligent Battery Management System (BMS) LIN Sensors in next-generation Ford vehicles. Responsibilities include design, development, integration, testing, and release of embedded software, collaborating with suppliers, and ensuring compliance with functional, cybersecurity, and quality standards. Requires expertise in embedded software, LIN protocols, battery state estimation, functional safety, and cybersecurity within the automotive industry.

The Material Flow Engineer will lead material flow initiatives within a high-paced, highly automated gigafactory for battery energy storage systems (BESS). This role focuses on managing and optimizing the supply chain for on-site material handling, supporting manufacturing process engineering to enhance safety, quality, and productivity. Responsibilities include applying engineering principles to optimize manufacturing and assembly processes, driving production throughput and line balancing, creating a culture of lean manufacturing, developing labor standards, conducting job ergonomics evaluations, and providing engineering support for material flow processes. The role also involves documenting standards, ensuring material availability, working with various departments (Planning, Production, Supply Chain), designing material flow processes and equipment, recommending improvements, leading plant layout changes, developing floor space analyses, and managing in-plant storage and call systems. The position requires a Bachelor's degree in Engineering (Industrial Engineering preferred) and 5+ years of manufacturing experience, with experience in Greenfield site development or high-volume automotive/battery/electronics manufacturing and Lean/Six Sigma certification being preferred.

This role focuses on defining and managing requirements for connected vehicle features and cloud-integrated services at Ford. It involves system ownership, bridging product requirements with vehicle engineering, cloud services, privacy, and supplier integration. The engineer will define technical, security, privacy, and regulatory requirements, govern cloud interfaces, manage customer authorization workflows, and ensure compliance with cybersecurity and privacy regulations. Responsibilities also include defining OTA update strategies, provisioning processes, and operational behavior for various connected features, as well as verifying supplier compliance and validating system functionality.

Supervise a team of calibration engineers responsible for the calibration development of the 2.5L xHEV powertrain control system and hybrid controller. Own the commodity calibration strategy, ensuring consistency and reusability across vehicle lines while balancing program-specific requirements, performance targets, emissions compliance, fuel economy, and drivability standards. Collaborate cross-functionally and manage team resources and development.

Product Development Engineer for RWD Hybrid Transmissions at Ford, responsible for integration into vehicle space, owning product delivery for cost, quality, and milestones from program initiation to launch. Key responsibilities include managing CAD/BOM structures, supplier data integration, CAD feasibility analysis, and leading testing and root cause investigations. Requires a Bachelor's degree in mechanical engineering and at least 2 years of automotive transmission experience.

This role is focused on leading the transformation of Ford's manufacturing operations, including engine, powertrain, battery, and vehicle assembly. It involves deploying Lean principles, driving digital transformation (Industry 4.0, IIoT, data analytics, automation), managing performance, and improving cost and efficiency. The role requires a blend of manufacturing depth, digital fluency, and change leadership.