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AI Engagement Lead – Global Manufacturing Electrical & SDV

at General Motors

General MotorsWarren, Michigan, United States of AmericaPosted 2026-06-15
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Job description

Job DescriptionAt General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.Global Manufacturing Electrical & SDV is looking for innovators who thrive in tough challenges and are passionate about tackling meaningful work that will shape the future of the automotive industry. This isn’t a role for those looking for an easy path—it’s for those who embrace change, push through obstacles, and take ownership of complex problems. While there will be long days and moments that test your resilience, you’ll find purpose in your work, flexibility to prioritize your family, and the support of a people-first culture. If you’re ready to grow, thrive, and make a real impact, we’d love to hear from you. WHY: You will enable plants to achieve world-class EFTQ, electrical performance, and SDV readiness by turning complex plant and electrical data into actionable insights and training that improve quality, efficiency, and cost on the plant floor.WHAT: You will lead the design, delivery, and adoption of AI, analytics, and training solutions that transform plant and electrical data into practical, easy-to-use tools for manufacturing teams.HOW: As the AI Engagement Lead, you will succeed in this role by partnering with plant and electrical stakeholders to prioritize high-value use cases, architect scalable AI and data solutions, and deliver hands-on training that embeds these tools into daily decision-making.Work Arrangement - Onsite The successful candidate is expected to report to the Warren Tech Center on a full-time basis. This role requires up to 70% domestic and international travel.What You’ll Do (Responsibilities):Build strong, trust-based relationships with plant stakeholders and deliver hands-on training that accelerates adoption of AI and analytics tools in partnership with the Process & Standards team.Align local initiatives with the global manufacturing strategy by standardizing data, KPIs, and best practices, and regularly report progress and results to central ME and leadership.Collaborate with Global Manufacturing Engineering to shape centralized strategy, roadmaps, best practices, and governance, ensure work is globally aligned and project tracking/reporting is transparent to the central ME team.Design and deliver end-to-end data, AI/ML, and BI solutions that improve manufacturing efficiency, quality, and overall operational performance.Use data, analytics, and AI solutions to identify root causes, predict potential failures, reduce defects, and improve End-of-Line Electrical First Time Quality (EFTQ) across manufacturing floors.Design, build, and maintain robust data pipelines and models (aligned with the Medallion architecture) to ensure accurate, reliable manufacturing and electrical data.Develop and maintain Power BI dashboards, reports, and paginated reports that give plant and leadership teams clear, actionable insights.Apply statistical and machine learning techniques to detect trends, predict issues, and enable proactive, data-driven decision-making.Integrate analytics and AI solutions into existing systems and plant workflows in close collaboration with IT, ME, and Quality teams.Your Skills and Abilities (Required Qualifications):Vehicle program launch and/or vehicle assembly manufacturing experience.Knowledge of manufacturing operation and quality systems.Strong collaboration and stakeholder-management skills.Experience designing and delivering training across diverse roles and organizational levels, enabling change management and accelerating adoption of digital and AI-driven tools.Proficiency in SQL and Power BI (including Power Query and DAX), including experience working with large, complex data sets.Excellent problem-solving, critical-thinking, and communication skills, with the ability to explain complex analysis to non-technical stakeholders.Demonstrated ability to thrive in a fast-paced environment with tight deadlines and frequently changing priorities.What Will Give You a Competitive Edge (Preferred Qualifications):3+ years of experience in data analytics within a manufacturing or industrial environment.3+ years of experience with end-to-end BI development (requirements, modeling, development, and deployment).3+ years of experience leading change management initiatives, including user training, communication, and driving adoption of analytics and BI solutions across diverse stakeholder groups.Experience with cloud-based data and analytics platforms (e.g., Databricks or similar).Vehicle program launch and/or vehicle assembly manufacturing experience.Demonstrated ability to integrate analytics and AI solutions into plants, MES, and IT systems and operational workflows.Proven track record of driving measurable business outcomes through data and AI.Bachelor’s degree or equivalent experience in computer science, data science, engineering. GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc). This role is categorized as onsite. This means the selected candidate is expected to report to a specific location on a full-time basis. The selected candidate will be required to travel at least 50% or more on a frequent basis.
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