2027 Summer Intern - Research and Development - AI/Machine Learning

General Motors; Mountain View (CA); Hybrid; USD 115,000 - 152,000; Full time

Job summary

General Motors seeks a PhD candidate for a summer intern role in Mountain View, CA. You will conduct original AI/ML research, build proofs-of-concept, and collaborate with GM R&D engineers to move promising ideas toward impact.

The role emphasizes deep research in areas like causal AI, neurosymbolic methods, world models, or related fields, with a focus on reproducibility, responsible AI, and clear communication of results to diverse audiences.

Qualifications

• Pursuit of a PhD in one of the listed areas.
• Must be a current student.
• Able to work full-time, 40 hours per week during the summer months.
• Demonstrated research depth, e.g. dissertation, publications, patents, or open-source work.
• Strong foundations in ML/DL with optimization and statistics.
• Experience with Python and ML frameworks (PyTorch/JAX/TensorFlow).
• Ability to formulate experiments, metrics, baselines, and communicate conclusions clearly.
• Strong verbal and written communication; able to collaborate with researchers, engineers, and stakeholders.
• Able to work on-site or in a hybrid research environment.

Responsibilities

• Conduct original research in advanced AI areas and develop practical methods.
• Translate challenges into research questions, hypotheses, and experiments.
• Design, implement, and evaluate ML models and POCs with engineering data.
• Develop methods for reasoning about physical systems, uncertainty, and complex interactions.
• Establish baselines and evaluation protocols; assess robustness and generalization.
• Build reproducible research code and data-processing workflows.
• Collaborate with GM R&D researchers to validate results and pathways to use.
• Communicate findings via reports, presentations, publications, and documentation.
• Contribute to research roadmaps and identify high-value experiments.
• Engage in a collaborative culture emphasizing reproducibility and responsible AI.

Skills

Machine learning foundations

Strong communication

Cross-disciplinary collaboration

Experience with experiments design

Education

Pursuit of a PhD in Computer Science / AI / ML / Applied Math / Statistics / Computational Science / Engineering / Physics

Must be a current student

Tools

Python

PyTorch

JAX

TensorFlow

Job description

Job Description

Conduct original research and develop practical AI/ML methods that accelerate GM’s research, engineering, and product development capabilities. This role is intended for a recent or soon-to-be-completed Ph.D. who brings strong depth in one or more advanced AI areas and the ability to work across disciplines. The intern will develop proof-of-concepts (POCs), evaluate them on meaningful engineering or scientific problems, communicate findings clearly, and collaborate with senior researchers and engineering partners to move promising ideas toward impact.

The Role

Conduct original research and develop practical AI/ML methods that accelerate GM’s research, engineering, and product development capabilities. This role is intended for a recent or soon-to-be-completed Ph.D. who brings strong depth in one or more advanced AI areas and the ability to work across disciplines. The intern will develop proof-of-concepts (POCs), evaluate them on meaningful engineering or scientific problems, communicate findings clearly, and collaborate with senior researchers and engineering partners to move promising ideas toward impact.

The Team

GM R&D is seeking an outstanding early-career intern to contribute to advanced work in Artificial Intelligence, Machine Learning, and Large Language Models. The role is designed for a fresh Ph.D. It emphasizes research depth, originality, experimental rigor, and growth toward independent technical leadership. The successful candidate will work with senior researchers, technical fellows, and engineering collaborators to formulate important problems, develop new methods, build research prototypes, and validate results. The work may span causal reasoning, neurosymbolic AI, world models, multimodal and generative AI, engineering agents, or related areas. The intern will be expected to connect theory and experimentation with real engineering needs while maintaining high standards for reproducibility, explainability, uncertainty awareness, and responsible AI.

What You’ll Do

• Conduct original research in one or more advanced AI areas such as causal AI, neurosymbolic AI, world models, multimodal or generative AI or engineering agents.
• Translate engineering and scientific challenges into well-defined 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 that can reason about physical systems, causal relationships, uncertainty, constraints, temporal evolution, or complex interactions among components.
• Establish meaningful baselines and evaluation protocols; analyze failure modes, robustness, generalization, interpretability, and uncertainty rather than relying only on headline accuracy.
• Build reproducible research code, data-processing workflows, and experiment pipelines using modern deep learning practices.
• Collaborate with GM R&D researchers and engineering partners to understand domain constraints, validate research results, and identify pathways from POCs to practical use.
• Communicate technical findings through research reports, presentations, publications, invention disclosures, demonstrations, and clear documentation.
• Contribute to technical discussions and research roadmaps by identifying promising approaches, important risks, and high-value experiments.
• Participate in a collaborative research culture that values intellectual curiosity, constructive peer review, responsible innovation, and continuous learning.

More About Who You Are

• A curious and intellectually rigorous researcher who enjoys working on difficult, open-ended problems.
• Deeply grounded in at least one technical area, while eager to learn and collaborate across adjacent AI, computational science, and engineering disciplines.
• Motivated by research that can create measurable value in real-world engineering workflows, not only benchmark performance.
• Comfortable moving between mathematical formulation, algorithm development, software implementation, and empirical validation.
• Able to explain complex ideas, assumptions, limitations, and results to both technical and general audiences.
• Independent in driving research tasks to completion while actively seeking feedback and working effectively with senior mentors and cross-functional teams.
• Committed to careful experimentation, reproducibility, safety, explainability, and responsible use of AI.

Required Qualifications

• Pursuit of a PhD in one of the following areas: 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 the 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.

Preferred Qualifications

• Research experience in causal inference, counterfactual reasoning, neurosymbolic methods and world models for engineering applications.
• Experience with multimodal AI, large language models, agentic systems, retrieval and reasoning, or AI-assisted engineering and software development.
• Evidence of research impact through high-quality publications, patents, invention disclosures, open-source contributions, awards, or successful technology demonstrations.
• Research or internship experience in automotive, mobility, aerospace, industrial, energy, defense, national laboratory, or university-industry collaboration settings.

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).

The position is subject to export control restrictions and requires the successful candidate to be a U.S. Person (U.S. citizen, U.S. permanent resident, asylee or refugee).

Work Arrangement

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Moutain View, CA three times per week, at minimum [or other frequency dictated by the business].

Compensation

The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position, as well as geography of the selected candidate.

The salary range for this role is $10,300–$13,600 monthly.

The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

GMwill provide aone-time lumpsum taxable stipend payment to eligible students selected for the2027Student Program - to help facilitate administration of relocation benefits, please apply using the permanent address you would move from.

Start dates for this internship role are May 24th & June 14th of 2027.

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