Summer Intern – AI/ML Engineer, Autonomous Vehicles, Simulation

General Motors

. Research and prototype advanced machine learning methods for perception, prediction, planning, or decision-making .

Posted 10/2/2026internshipSunnyvale • California • United StatesEntry Level💰 $12,300 - $14,600 per monthWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in machine learning and artificial intelligence, with a strong focus on model design, evaluation, and optimization for autonomous systems. Proficient in Python and ML frameworks, with a solid foundation in research methodologies and collaboration across engineering disciplines.

Highest-signal resume keywords

PhD Candidate In Computer ScienceProficiency In PythonExperience With PyTorch Or TensorFlowStrong Understanding Of Machine Learning MethodsResearch In Autonomous Vehicles

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningModel OptimizationData Pipeline DevelopmentExperiment DesignQuantitative Problem-SolvingProgramming FundamentalsStatistical EstimationNumerical OptimizationPerformance Analysis

Soft Skills

Strong Communication SkillsCollaboration Across Disciplines

Tools & Technologies

PyTorchTensorFlowJAXCUDAGPU ProgrammingHigh-Performance Computing

Industry Keywords

Autonomous VehiclesADASComputer VisionMultimodal LearningReinforcement LearningSimulation ValidationTrajectory PredictionBehavior PlanningMotion PlanningStructured Scene Understanding

Tech Stack

Tools & technologies

PythonPyTorchTensorflowC++

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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 ability to collaborate across research and engineering disciplines
Availability to work full-time, 40 hours per week, during the internship period
Preferred: research in autonomous vehicles, ADAS, robotics, computer vision, or embodied AI
Preferred: knowledge of foundation models, transformers, generative and diffusion models, or vision-language architectures
Preferred: multimodal learning with camera, lidar, radar, or other sensor data
Preferred: self-supervised, imitation, reinforcement, or deep reinforcement learning
Preferred: distributed, parallel, or high-performance computing environments
Preferred: ML systems, data pipelines, experimentation frameworks, or production-oriented model infrastructure
Preferred: simulation, closed-loop environments, or real-world driving scenario validation
Preferred: trajectory prediction, behavior planning, motion planning, perception, mapping, or structured scene understanding
Preferred: C++ or other systems programming languages
Preferred: GPU programming, CUDA, accelerator frameworks, or performance profiling
Preferred: numerical optimization, statistical estimation, probabilistic modeling, and systems-level tradeoff analysis
Preferred: first-authored publications, grants, fellowships, patents, or open-source contributions

Benefits

Comp & perks

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