Summer Systems Engineer Intern - Auto & ADAS (Onsite)

General Motors Corporation; Milford Charter Township (MI); Hybrid; USD 97,000 - 104,000; Full time

Benefits offered by this job

Paid US GM Holidays

GM Family First Vehicle Discount

Intern events to network with leaders

Job summary

General Motors Corporation is offering a 2027 Summer Intern position in Systems Engineering, with on-site work in Milford and Warren, Michigan. You will join the AV Systems, Sensing and Integration Team and contribute to definition, integration and validation of advanced driving features.

The role emphasizes collaboration across disciplines, development of test scripts, and automation of validation activities, with opportunities to work on real prototypes and data-driven analyses.

Qualifications

• Pursuit of a Bachelor's or Master's degree in Computer Science or Engineering.
• Must be graduating between December 2027 and August 2028.
• Coursework or project experience in Python or MATLAB or embedded microcontrollers.
• Able to work fulltime, 40 hours per week.

Responsibilities

• Define use cases and system requirements for AV sensing and integration.
• Support architecture development and interface definitions for subsystems.
• Collaborate with software teams to integrate hardware and software.
• Prepare test plans and automate in-vehicle or bench testing.
• Develop scripts to automate testing on development vehicles and benches.

Skills

Python

MATLAB

Embedded systems

Education

Bachelor's or Master's degree in Computer Science or Engineering

Tools

MATLAB/Simulink

Job description

General Motors Corporation is offering a 2027 Summer Intern position in Systems Engineering, with on-site work in Milford and Warren, Michigan. You will join the AV Systems, Sensing and Integration Team and contribute to definition, integration and validation of advanced driving features.

The role emphasizes collaboration across disciplines, development of test scripts, and automation of validation activities, with opportunities to work on real prototypes and data-driven analyses.