R&D Researcher – AI and Machine Learning
About the position
The R&D Manufacturing Systems Research Group at General Motors is seeking a researcher to develop and apply artificial intelligence and machine learning (AI/ML) solutions for advanced manufacturing systems. The role addresses real-world manufacturing challenges involving process improvement, quality, automation, production efficiency, and decision support. The researcher will work with multidisciplinary teams to identify opportunities, translate manufacturing and engineering challenges into research questions and technical plans, develop concepts and prototypes, evaluate results, and help transition promising solutions into manufacturing applications. Work includes conducting applied research and technical development at the intersection of AI/ML and manufacturing systems, evaluating emerging technologies, and assessing technical and business impact. The selected candidate is expected to report to a specific location at least three times a week, or at another frequency set by their manager. Relocation benefits are available to candidates who qualify under company policy. GM does not provide immigration-related sponsorship for this role.
Responsibilities
- Conduct applied research and technical development at the intersection of AI/ML and manufacturing systems.
- Partner with researchers, manufacturing engineers, plant personnel, operations teams, and external collaborators to identify opportunities and develop practical solutions.
- Develop and evaluate AI/ML models for manufacturing engineering and production applications.
- Build data pipelines, prototypes, analytical tools, and decision-support solutions.
- Apply methods including machine learning, deep learning, generative AI, large language models, computer vision, time-series modeling, and optimization.
- Work with manufacturing data from sensors, equipment, processes, simulations, and operational systems.
- Translate engineering and manufacturing challenges into research questions and technical plans.
- Design experiments, validate results, and assess technical and business impact.
- Evaluate emerging AI/ML technologies for their potential value to GM manufacturing systems.
- Collaborate with cross-functional teams, universities, suppliers, and technical experts.
- Communicate results through presentations, reports, publications, and invention disclosures.
- Stay current on AI/ML methods, tools, and responsible AI practices.
Requirements
- Master’s degree or PhD in computer science, artificial intelligence, machine learning, data science, engineering, applied mathematics, physics, or a related field.
- Experience developing and evaluating AI/ML models through academic or industrial research, internships, or applied engineering projects.
- Proficiency in Python and experience with AI/ML frameworks or analytical tools.
- Knowledge of data preparation, model training, validation, performance evaluation, and experiment design.
- Experience working with structured or unstructured data, such as sensor, time-series, image, text, or process data.
- Strong analytical, problem-solving, communication, and collaboration skills.
- Ability to work independently and contribute effectively to a multidisciplinary research team.
Nice-to-haves
- Experience applying AI/ML to manufacturing, engineering, robotics, automation, scientific computing, or industrial operations.
- Knowledge of manufacturing process modeling, process control, quality systems, production systems, optimization, or operations research.
- Experience with computer vision, anomaly detection, predictive maintenance, digital twins, simulation, reinforcement learning, generative AI, large language models, or agentic systems.
- Experience with tools such as PyTorch, TensorFlow, scikit-learn, Keras, MATLAB, R, SQL, or cloud-based AI/ML platforms.
- Experience designing data architectures, integrating databases, or deploying models into operational environments.
- Familiarity with MLOps, model monitoring, model lifecycle management, and responsible AI.
- Peer-reviewed publications, conference presentations, patents, or invention disclosures.
- Experience collaborating with universities, suppliers, research institutions, or distributed technical teams.
Benefits
- Relocation benefits are available for candidates who qualify under company policy.
- GM provides resources to support employee well-being at work and at home.
