2027 Summer Intern: Software Engineer, AV/AI Platform

GM's Autonomous Vehicle Platform Software Engineering organization builds the foundational software that enables autonomous-driving capabilities to run reliably on production vehicle platforms. The teams span platform operating systems and compute drivers, embedded MCU software, core services and tools, and system-performance engineering. Their work includes developing low-level platform software, middleware, service interfaces, software-update and deployment capabilities, diagnostics, logging and observability, and performance tooling across vehicle compute systems.

Working at the intersection of software, hardware, AI/ML, and vehicle systems, the teams integrate operating systems, sensors, compute, and application workloads to deliver secure, efficient, testable, and production-ready autonomous-vehicle capabilities. Engineers collaborate closely with AV, AI/ML, hardware, systems, validation, and safety partners, with opportunities to contribute across embedded software, platform engineering, developer tools, and performance optimization. Depending on team needs, projects may focus on platform OS and drivers, MCU software, core services, vehicle software integration, or system and ML-workload performance.

About the Role

As an Autonomous Driving Software Engineer Intern, you will contribute to the design, development, and validation of cutting-edge software powering self-driving systems. You'll collaborate with experienced engineers across AV Platform teams to build scalable, safety-critical software for autonomous vehicles operating in real-world environments.

What You'll Do

• Develop, test, and deploy production-ready code across components of vehicle platform software.
• Quickly ramp up on assigned codebase, product area, and/or system.
• Complete assigned tasks efficiently with few iterations.
• Identify problem statements, outline optimal solutions, account for tradeoffs and edge cases.
• Participate in design reviews, code reviews, technical discussions, and continuous integration and deployment practices.
• Collaborate with cross-functional teams including hardware, systems, test, and safety to ensure seamless software integration.
• Communicate effectively across multiple stakeholders.

Required Qualifications

• Currently enrolled in a full-time, degree-seeking program and in the process of obtaining a Bachelor's or Master's degree in computer science, artificial intelligence, machine learning, robotics, engineering, or a related STEM field.
• Must be graduating between December 2027 and August 2029 and have at least one additional quarter/semester of school remaining following the completion of the internship.
• Availability to work full-time, 40 hours per week, during the 12 week summer internship period between May 24th – August 13th or June 14th – September 3rd 2027.
• Strong foundation in algorithms and data structures, with proficiency in C++, Python, or another object-oriented programming language.
• Strong written and verbal communication skills and the ability to collaborate across teams.

Preferred Qualifications

• Demonstrated software engineering experience through an internship, work experience, coding competition, student engineering team or competition (e.g., SAE student competitions, EcoCAR, Formula SAE, or Baja SAE), research, coursework, or personal project.
• Experience building, testing, and shipping production software, with exposure to safety-critical development (FDA, FAA, Automotive).
• Familiarity with embedded build systems such as Yocto or Buildroot, networking fundamentals, and software integration across compute, MCU, and vehicle platforms.
• Understanding of networking fundamentals relevant to embedded or distributed systems.
• Experience with robotics frameworks (e.g., ROS), embedded Linux platforms, or common sensors (e.g., cameras, lidar, radar, IMUs) is a plus.
• Passion for self-driving technology and its potential impact on the world.

Work Arrangement

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to their designated office three times per week, at minimum.