Descrição
The Role
The R&D Manufacturing Systems Research Group at General Motors is seeking a researcher to develop and apply artificial intelligence and machine learning solutions for advanced manufacturing systems.
This role will focus on applying AI/ML to real-world manufacturing challenges involving process improvement, quality, automation, production efficiency, and decision support. The researcher will work with multidisciplinary teams to develop new concepts, build prototypes, evaluate results, and help transition successful solutions into manufacturing applications.
What You Will Do
You will conduct applied research and technical development at the intersection of AI/ML and manufacturing systems. You will collaborate with researchers, manufacturing engineers, plant personnel, operational teams, and external partners to identify opportunities and develop practical solutions.
Key Responsibilities
· 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 and determine their potential value for GM manufacturing systems.
· Collaborate with cross-functional teams, universities, suppliers, and technical experts.
· Communicate technical results through presentations, reports, publications, and invention disclosures.
· Maintain current knowledge of AI/ML methods, tools, and responsible AI practices.
Required Qualifications
· 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 research, 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.
Preferred Qualifications
· 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 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.
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.)
Esta função é classificada como híbrida. Isso significa que o candidato selecionado deverá trabalhar no escritório/fábrica da GM pelo menos 3 vezes por semana {ou outra frequência ditada por seu gerente}.
Benefícios de realocação estão disponíveis para candidatos que se qualificarem de acordo com a política da empresa.
Informações sobre diversidade
A General Motors está comprometida em ser um local de trabalho que não só é livre de discriminação ilegal, como estimula verdadeiramente a inclusão e integração. Acreditamos enfaticamente que a diversidade na força de trabalho cria um ambiente no qual nossos colaboradores podem crescer e desenvolver melhores produtos para nossos clientes. Incentivamos os candidatos interessados a analisar as principais responsabilidades e qualificações de cada função e a se candidatar a qualquer cargo que corresponda a suas habilidades e capacidades. Os candidatos no processo de recrutamento podem, quando aplicável, ser solicitados a concluir com sucesso uma ou mais avaliações relacionadas à função e/ou uma seleção pré-emprego antes de iniciar o emprego. Para saber mais, acesse Como contratamos.
Declaração de Igualdade de Oportunidades de Emprego (EUA)
A General Motors tem orgulho de ser um empregador que oferece oportunidades iguais. Todos os candidatos qualificados serão considerados para o emprego, independentemente de raça, cor, religião, sexo, orientação sexual, identidade de gênero, origem nacional, deficiência ou status como veterano protegido.
Adaptações (EUA e Canadá)
A General Motors oferece oportunidades a todos os candidatos a emprego, incluindo pessoas com deficiências. Se você precisa de uma adaptação razoável para ajudá-lo na sua pesquisa de cargos ou solicitação de emprego, fale conosco pelo e-mail [email protected] ou pelo telefone 800-865-7580. No seu e-mail, inclua uma descrição da adaptação específica que você está solicitando assim como o nome do cargo e o número de requisição do cargo ao qual está se candidatando.