Job DescriptionPosition: AI/ML Senior Researcher - Smart Manufacturing Systems Research GroupWho We AreThe Materials & Manufacturing Systems Research Lab at the General Motors R&D Center located in Warren, Michigan is seeking a technically exceptional AI/ML Senior Researcher with world class, Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), World Models, and Agentic AI skills to perform leading edge research in the area of Smart Manufacturing Systems.
This is an exciting growth area at GM R&D where researchers will be part of a dynamic team focused on improving GM's advanced manufacturing capabilities. Assignments will vary depending on background, but they will be expected to provide immediate technical and professional leadership in assignments to identify, define, and develop future strategic applications of AI into GM's future factory operations.
Researchers are also expected to counsel GM engineering management on manufacturing engineering process, practice and tool improvements, as well as carry out leadership roles in GM programs and/or projects. They will likely represent GM in a variety of research activities with contractors and academic collaborators, and at other GM Centers, and external agencies and technical organizations. In addition, researchers are expected to develop a strong record of invention, publishing and presenting.
The specific research focus of the Smart Manufacturing Research Group is to develop advanced AI/ML, Agentic AI, mathematical modeling and optimization approaches and build real-time, decision support tools that enable GM's plants to meet efficiency and quality goals. In this role, you will work hands-on to architect, build, deploy, and scale AI/ML models, agents, agentic systems that address complex manufacturing engineering and operations challenges. The ideal candidate is comfortable developing production-grade AI/ML solutions, evaluating emerging technologies, and engaging senior leaders in clear, actionable discussions on strategy, roadmap, and business impact. A background in manufacturing systems and process design, smart manufacturing, digital twins, simulation, statistics, quality management, control systems and machine vision would also be highly desirable. Experience with production operations is a plus.
What You Will Do- Build, validate, deploy, and scale AI/ML models for high-impact manufacturing engineering, research and development applications.
- Lead technical work across a broad set of AI domains, including classical machine learning, deep learning, GenAI, Large Language Models, multimodal AI, agentic AI, World Models, and physics-based AI.
- Translate business and engineering problems into practical AI/ML solution strategies and executable technical plans.
- Serve as a technical authority on model development, deployment architectures, data strategy, evaluation methods, and responsible AI practices.
- Generate new concepts and ideas while conducting research programs that apply the latest AI/ML tools
- Drive technical assignments in a resourceful and timely manner with minimal supervision
- Work well with fellow researchers, centers, operational groups, plant personnel and universities.
- Maintain state-of-art technical skills and knowledge
- Develop working relationships with internal and external subject matter experts
- Effectively communicate and detail results through internal and external publication
- Collaborate with global technical teams and lead discussions as an expert in manufacturing AI/ML
More About Who You Are- Recognized technical expert in AI/ML with the ability to span research, applied development, and deployment.
- Strong strategic thinker who can connect technical opportunities to business value and organizational priorities.
- Able to assess emerging AI capabilities pragmatically and distinguish hype from scalable business value.
- Passionate about applying advanced AI to challenging real-world manufacturing engineering and scientific problems.
- Effective at framing technical decisions, risks, and recommendations in ways that support executive decision-making.
What You Need- PhD or advanced degree in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Engineering, Physics, or a related field, with significant relevant experience.
- Demonstrated success building and deploying AI/ML models in production or high-value applied research environments.
- Deep expertise across multiple AI domains, including machine learning, deep learning, LLMs, generative AI, world models, and physics-based machine learning.
- Strong understanding of modern AI/ML development workflows, including data pipelines, model training, evaluation, deployment, monitoring, and lifecycle management.
- Experience applying AI/ML to complex technical domains such as engineering, simulation, scientific computing, and advanced manufacturing engineering.
- Background in manufacturing process modeling, design, control, and optimization
- Manufacturing engineering theory and principles of production management & operations
- Excellent collaborative skills
- Proven record of high impact publications in peer-reviewed conferences/journals
What Would Be Even Better- PhD in relevant field of study
- 0-6 years of research experience beyond PhD. (university, research institution, or industrial research)
- Background in manufacturing process modeling, design, control, and optimization with track record of successful manufacturing implementations
- Proficient in data manipulation, analysis, and visualization
- Structured database design and integration experience along with programming skills (e.g. SQL, C++, Python, R, Matlab)
- Familiarity with AI tools: Scikit Learn, Tensorflow, Keras, PyTorch
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 hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.This job may be eligible for relocation benefits.
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