General Motors
2027 Summer Intern – Machine Learning Engineer, AV/AI Platform
Sunnyvale, California, United States of America · Hybrid · Internship · Posted Oct 2, 2026
- Experience
- No minimum number of years stated.
- Education
- Currently enrolled in a full-time, degree-seeking bachelor's or master's program in computer science, artificial intelligence, machine learning, robotics, engineering, or a related STEM field.
About the job
Develop and optimize AI training-platform infrastructure, data pipelines, model workflows, and testing tools for autonomous-driving and advanced driver-assistance systems.
What you'll do
- Build infrastructure and tools for model training, edge deployment, regression, and inference.
- Improve data processing, training and inference workflows, testing, instrumentation, and monitoring.
- Adapt machine-learning methods for parallel environments and collaborate with engineers on requirements and feature roadmaps.
What they ask for
- Currently pursuing a bachelor's or master's degree in a related STEM field; graduating December 2027–August 2029, with at least one academic term remaining after the internship.
- Available full-time (40 hours/week) for a 12-week summer internship during one of the stated 2027 periods.
- Strong algorithms and data structures foundation; proficiency in C++, Python, or another object-oriented language.
- Coursework, project, research, or applied experience in AI or machine learning; experience with algorithms, software development, or systems engineering fundamentals.
Nice to have
- Software-engineering or relevant research/work experience; relevant areas include autonomy, robotics, embedded software, controls, simulation, sensor data, or ML.
- Exposure to AI-assisted development tools, distributed systems or ML infrastructure, or accelerator programming.
Pay
$8,100 – 11,800 per month (base salary)
Tools
C++, Python, Spark, Ray, Kubernetes, Slurm, PyTorch, TensorRT
AI focus
Build and optimize AI training infrastructure and workflows; accelerate model training and inference, improve data processing and evaluation, and support autonomous-driving and active-safety systems.
Model-written summary · the original posting is authoritative