AI/ML Senior Researcher
Role details
Job location
Tech stack
Job description
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., * 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, 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}.
Requirements
- 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., * 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