2027 Summer Intern – AI/ML Engineer, Autonomous Vehicles: Simulation (PhD)

generalmotors; Sunnyvale (CA); Hybrid; USD 137,000 - 163,000; Full time

Benefits offered by this job

Paid US GM Holidays

GM Family First Vehicle Discount

Growth potential within GM

Intern events to network

Job summary

General Motors invites applications for a PhD AI/ML Engineering Intern to advance reliable AI/ML capabilities for autonomous vehicle systems. You will translate deep research into production-oriented solutions spanning perception, planning, and decision-making using real driving data and simulation.

You will design experiments, build models, and contribute to data pipelines and evaluation tools, collaborating across research and engineering teams in a hybrid work setup.

Qualifications

• Currently enrolled full-time in a PhD program in computer science, machine learning, artificial intelligence, robotics, engineering, or a related STEM field.
• Must have at least one additional quarter/semester of school remaining following the completion of the internship.
• Demonstrated depth of AI/ML research through publications, research projects, advanced coursework, or equivalent technical work.
• Strong understanding of modern machine learning and deep learning methods.
• Proficiency in Python and hands on experience with an ML framework such as PyTorch, TensorFlow, or JAX.
• Experience designing experiments, analyzing results, and applying quantitative problem solving methods.
• Strong programming, debugging, and software development fundamentals.
• Strong communication skills and the ability to collaborate across research and engineering disciplines.
• Availability to work full-time, 40 hours per week, during the internship period.

Responsibilities

• Research and prototype advanced machine learning methods for perception, prediction, planning, or decision-making.
• Design, train, evaluate, and improve models using large-scale multimodal driving and sensor data.
• Build data pipelines, experimentation workflows, and evaluation tools for rapid model iteration.
• Validate models through simulation, testing, performance analysis, and failure-case investigation.
• Optimize models and systems for scalability, latency, reliability, and deployment constraints.
• Collaborate with engineering and research partners to integrate prototypes into autonomous vehicle systems.
• Document findings, present technical insights, and contribute to publications or other research outputs.

Skills

Python

ML research

Experimental design

Communication

Collaboration

Debugging

Programming

Education

PhD in CS/ML/AI/Robotics

Tools

PyTorch

TensorFlow

JAX

Job description

Job Description

About the role

As a PhD AI/ML Engineering Intern within General Motors’ Autonomous Vehicles organization, you will advance reliable AI/ML capabilities by translating deep research into validated, production-oriented systems. Your work may support perception, prediction, planning, decision-making, embodied AI, simulation, sensor understanding, mapping, or large-scale model development. You will work with real-world driving and sensor data, modern machine learning methods, and autonomous vehicle evaluation environments. You will collaborate with researchers and engineers to design experiments, build and assess models, investigate failure cases, and integrate promising approaches into broader AV systems.

What you’ll do

• Research and prototype advanced machine learning methods for perception, prediction, planning, or decision-making.
• Design, train, evaluate, and improve models using large-scale multimodal driving and sensor data.
• Build data pipelines, experimentation workflows, and evaluation tools for rapid model iteration.
• Validate models through simulation, testing, performance analysis, and failure-case investigation.
• Optimize models and systems for scalability, latency, reliability, and deployment constraints.
• Collaborate with engineering and research partners to integrate prototypes into autonomous vehicle systems.
• Document findings, present technical insights, and contribute to publications or other research outputs.

Required qualifications

• Currently enrolled full-time in a PhD program in computer science, machine learning, artificial intelligence, robotics, engineering, or a related STEM field.
• Must have at least one additional quarter/semester of school remaining following the completion of the internship
• Demonstrated depth of AI/ML research through publications, research projects, advanced coursework, or equivalent technical work.
• Strong understanding of modern machine learning and deep learning methods.
• Proficiency in Python and hands on experience with an ML framework such as PyTorch, TensorFlow, or JAX.
• Experience designing experiments, analyzing results, and applying quantitative problem solving methods.
• Strong programming, debugging, and software development fundamentals.
• Strong communication skills and the ability to collaborate across research and engineering disciplines.
• Availability to work full-time, 40 hours per week, during the internship period.

Preferred qualifications

• Candidates are not expected to meet every qualification listed below. Depending on the needs of a specific Autonomous Vehicles team, a combination of these skills and areas of knowledge may be relevant.
• Conduct research in autonomous vehicles, ADAS, robotics, computer vision, or embodied AI.
• Demonstrate knowledge of foundation models, transformers, generative and diffusion models, or vision-language architectures.
• Apply multimodal learning techniques to camera, lidar, radar, or other sensor data.
• Use self supervised, imitation, reinforcement, or deep reinforcement learning methods.
• Train models on large-scale datasets using distributed, parallel, or high-performance computing environments.
• Develop ML systems, data pipelines, experimentation frameworks, or production-oriented model infrastructure.
• Validate models through simulation, closed-loop environments, or real-world driving scenarios.
• Apply expertise in trajectory prediction, behavior planning, motion planning, perception, mapping, or structured scene understanding.
• Program in C++ or other systems programming languages.
• Optimize models and systems using GPU programming, CUDA, accelerator frameworks, or performance profiling.
• Apply numerical optimization, statistical estimation, probabilistic modeling, and systems-level tradeoff analysis.
• Demonstrate a strong research record through first-authored publications, grants, fellowships, patents, or open-source contributions.

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 compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

• The salary range for this role is $12,300-$14,600 per month. 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.

What you’ll get from us (Benefits):

• Paid US GM Holidays
• GM Family First Vehicle Discount Program
• Result-based potential for growth within GM
• Intern events to network with company leaders and peers

Work Arrangement:

• Start dates for this internship role are May 24th and June 14th of 2027.
• Assignments will be based on team placement to ensure interns are located with their working team and leader.
• Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to their designated work location three times per week, at minimum.

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