Hybrid Autonomy Intern: Perception & Planning

General Motors Company; Sunnyvale (CA); Hybrid; USD 132,000 - 163,000; Full time

Benefits offered by this job

Paid U.S. GM holidays

GM Family First Vehicle Discount

Intern events and networking

Job summary

General Motors is seeking an Onboard Autonomy Intern in Sunnyvale, CA to contribute to focused research or engineering projects within the onboard driving stack. You will prototype, evaluate, and improve algorithms or software using vehicle data, simulation, or production-oriented environments.

You will work with experienced researchers and engineers on sensor fusion, perception, ML planning, and local planning, gaining hands-on experience in production-oriented autonomy systems.

Qualifications

• Pursuing a Master’s or Ph.D. in CS, Robotics, EE, ME, Controls, ML.
• Experience in ML, CV, robotics, controls, optimization, or autonomous systems.
• Strong Python and C++ skills.
• Strong analytical and collaboration skills.
• Available to work full-time, 40 hours/week during the internship.

Responsibilities

• Prototype and evaluate algorithms for perception, prediction, planning, trajectory generation, controls, or integration.
• Work with real-world driving data and simulation to measure performance and investigate failures.
• Build data-processing, visualization, testing, and evaluation tools.
• Contribute to production-quality software through design reviews, code reviews, automated testing, CI, and documentation.
• Analyze results, improve system performance, collaborate across disciplines, and present findings.

Skills

Python

C++

Machine Learning

Communication

Collaboration

Education

Master’s or Ph.D. in CS/Robotics/EE/ME/Controls/ML

Tools

ROS

PyTorch

TensorFlow

Job description

General Motors is seeking an Onboard Autonomy Intern in Sunnyvale, CA to contribute to focused research or engineering projects within the onboard driving stack. You will prototype, evaluate, and improve algorithms or software using vehicle data, simulation, or production-oriented environments.

You will work with experienced researchers and engineers on sensor fusion, perception, ML planning, and local planning, gaining hands-on experience in production-oriented autonomy systems.