Autonomous Vehicles AI/ML Engineer (PhD Internship)

General Motors; Sunnyvale (CA); Hybrid; USD 148,000 - 175,000; Full time

Benefits offered by this job

Paid Holidays

Vehicle Discount Program

Growth opportunities

Networking events

Job summary

General Motors’ Autonomous Vehicles organization seeks a PhD AI/ML Engineering Intern to translate research into production-grade systems for perception, prediction, planning, and embodied AI using real-world driving data and evaluation environments.

You will collaborate with researchers to design experiments, build and assess models, and integrate prototypes into broader AV systems, with hybrid work and an early-2027 start.

Qualifications

• Currently enrolled in a PhD program in a relevant STEM field.
• At least one additional quarter/semester remaining after internship.
• Demonstrated AI/ML research through publications or projects.
• Strong grasp of modern ML and deep learning methods.
• Proficient in Python with ML framework experience.
• Experience designing experiments and analyzing results.
• Strong collaboration and communication skills.

Responsibilities

• Research and prototype advanced ML methods for perception, prediction, planning, or decision-making.
• Design, train, evaluate, and improve models using large-scale driving and sensor data.
• Build data pipelines, experiments, and evaluation tools for rapid iterations.
• Validate models via simulation, testing, and failure-case analysis.
• Optimize models and systems for scalability, latency, and deployment constraints.
• Collaborate with engineering and research teams to integrate prototypes.
• Document findings and contribute to publications or research outputs.

Skills

Python proficiency

ML frameworks

Experiment design

Strong programming

Communication skills

Education

PhD in CS/ML/AI/Robotics

At least one semester remaining

Tools

PyTorch

TensorFlow

JAX

CUDA

Job description

General Motors’ Autonomous Vehicles organization seeks a PhD AI/ML Engineering Intern to translate research into production-grade systems for perception, prediction, planning, and embodied AI using real-world driving data and evaluation environments.

You will collaborate with researchers to design experiments, build and assess models, and integrate prototypes into broader AV systems, with hybrid work and an early-2027 start.