Summer Intern, Research and Development – AI/Machine Learning

General Motors

. Conduct original research in advanced AI areas including causal AI, neurosymbolic AI, world models, multimodal or generative AI, and engineering agents .

Posted 10/12/2026internshipMountain View • California • United StatesEntry Level💰 $10,300 - $13,600 per monthWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced AI research areas such as Causal AI, Generative AI, and Machine Learning, with strong foundations in Python and frameworks like PyTorch and TensorFlow. Capable of translating complex engineering challenges into research methodologies and effectively communicating findings to diverse stakeholders.

Highest-signal resume keywords

PhD In Computer ScienceMachine LearningDeep LearningPython DevelopmentResearch Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Causal AIGenerative AINeurosymbolic AIMachine Learning ModelsExperimental DesignData Processing WorkflowsOptimizationProbability/StatisticsNumerical MethodsScientific Computing

Soft Skills

Verbal CommunicationWritten CommunicationCollaboration

Tools & Technologies

PyTorchJAXTensorFlow

Industry Keywords

Research DepthTechnical ContributionsPeer ReviewResponsible InnovationContinuous Learning

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

Conduct original research in advanced AI areas including causal AI, neurosymbolic AI, world models, multimodal or generative AI, and engineering agents
Translate engineering and scientific challenges into research questions, hypotheses, algorithms, and experimental plans
Design, implement, and evaluate machine learning models and proof-of-concepts using real, simulated, experimental, or engineering data
Develop methods addressing physical systems, causal relationships, uncertainty, constraints, temporal evolution, and complex component interactions
Establish baselines and evaluation protocols; analyze failure modes, robustness, generalization, interpretability, and uncertainty
Build reproducible research code, data-processing workflows, and experiment pipelines
Collaborate with GM R&D researchers and engineering partners to validate results and move proof-of-concepts toward practical use
Communicate findings through research reports, presentations, publications, invention disclosures, demonstrations, and documentation
Contribute to technical discussions and research roadmaps
Participate in collaborative research, peer review, responsible innovation, and continuous learning

Requirements

What you’ll need

Pursuit of a PhD in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Computational Science, Engineering, Physics, or a related field
Must be a current student
Able to work fulltime, 40 hours per week during the summer months
Demonstrated research depth in at least one relevant area, supported by a dissertation, publications, patents, open-source work, research software, or comparable technical contributions
Strong foundations in machine learning and deep learning, with working knowledge of optimization, probability/statistics, numerical methods, or scientific computing as appropriate to the research area
Experience developing and evaluating models in Python and frameworks such as PyTorch, JAX, TensorFlow, or comparable tools
Ability to formulate experiments, select appropriate metrics and baselines, analyze results, and communicate technical conclusions with appropriate caveats
Strong verbal and written communication skills and ability to collaborate effectively with researchers, engineers, and technical stakeholders
Ability to work on-site or in a hybrid research environment in accordance with GM work practices and project needs
No GM immigration-related sponsorship now or in the future
Must be a U.S. Person (U.S. citizen, U.S. permanent resident, asylee, or refugee) due to export control restrictions

Benefits

Comp & perks

One-time lump sum taxable stipend payment to eligible students to help facilitate relocation benefits
Hybrid work arrangement