Autonomy Intern: Real-Time Perception & Planning

General Motors; Sunnyvale (CA); Hybrid; USD 132.000 - 163.000; Vollzeit

Benefits dieser Stelle

Paid U.S. GM holidays

GM Family First Vehicle Discount

Zusammenfassung

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

You will work with researchers and engineers on perception, planning, and controls, engaging in data-driven analysis, tool building, and code reviews to advance real-time autonomy systems.

Qualifikationen

• Pursuing a Master’s or Ph.D. in a STEM field with relevant coursework or research.
• Experience in ML, CV, robotics, controls, optimization, or autonomous systems.
• Strong Python skills and proficiency in C++ or another systems language.
• Demonstrated teamwork, communication, and collaboration abilities.

Aufgaben

• 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, testing, CI, and documentation.

Kenntnisse

Python

C++

Machine Learning

Robotics

Communication

Ausbildung

Master’s or Ph.D. in Computer Science, Robotics, Electrical or Mechanical Engineering, Controls, Machine Learning, or related STEM field

Tools

ROS

PyTorch

TensorFlow

Jobbeschreibung

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

You will work with researchers and engineers on perception, planning, and controls, engaging in data-driven analysis, tool building, and code reviews to advance real-time autonomy systems.