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

General MotorsGeneral MotorsMountain View, California, United States
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Posted

10/12/2026

Employment

Full time, Internship

Range

$10k - $14k/month

Work style

Hybrid

3 days in office

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AI summary

Core responsibilities

The intern will conduct original research and develop practical AI/ML methods to accelerate GM's engineering and product development capabilities. They will design, implement, and evaluate proof-of-concepts while collaborating with senior researchers to validate results and communicate findings.

Requirements overview

Candidates must be current PhD students in a relevant technical field with strong foundations in machine learning and deep learning. Proficiency in Python and deep learning frameworks is required, along with the ability to work on-site in a hybrid capacity.

Key skills

Artificial IntelligenceMachine LearningLarge Language ModelsPythonPyTorchJAXTensorFlowCausal InferenceNeurosymbolic AIGenerative AIMultimodal AIData AnalysisExperimental DesignResearchSoftware DevelopmentProblem Solving

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Education requirements

postgraduate degree

About General Motors

Industry

Motor Vehicle Manufacturing

Employees

118,300

Type

Public Company

Size

10,001+ employees

General Motors’ vision is to create a world with Zero Crashes, Zero Emissions and Zero Congestion, and we have committed ourselves to leading the way toward this future. Today, we are in the midst of a transportation revolution, and we have the ambition, the talent and the technology to realize the safer, better and more sustainable world we want. As an open, inclusive company, we’re also creating an environment where everyone feels welcomed and valued for who they are. One team, where all ideas are considered and heard, where everyone can contribute to their fullest potential, with a culture based in respect, integrity, accountability and equality. Our team brings wide-ranging perspectives and experiences to solving the complex transportation challenges of today and tomorrow. For information on the GM Privacy Statement, please visit http://www.gm.com/privacy-statement.html

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Job categories

Science & ResearchTechnologySoftwareEngineeringData & Analytics

Description

Job Description 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. GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2027 Student 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. About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Requirements

  • •Artificial Intelligence
  • •Machine Learning
  • •Large Language Models
  • •Python
  • •PyTorch
  • •JAX
  • •TensorFlow
  • •Causal Inference
  • •Neurosymbolic AI
  • •Generative AI
  • •Multimodal AI
  • •Data Analysis
  • •Experimental Design
  • •Research
  • •Software Development
  • •Problem Solving

Benefits

  • •Relocation stipend

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