2027 Summer Intern – Software Verification Engineer, AV/AI Platform

Job Description

About the Team: 

AV Platform System Integration and Validation team is responsible for defining, implementing, and optimizing system integration & validation to ensure the quality, safety, and reliability of the AV platform software. We combine deep expertise in hardware, software features, and vehicle systems engineering to ensure the quality, safety, and reliability of the ADAS/AV platform software.  

 

About the Role: 

As an Autonomous Driving System Integration & Validation Intern, you will contribute to the integration, testing, and validation of software and hardware systems that power autonomous vehicles. You’ll collaborate with experienced engineers across AV Platform teams to bring up complex systems, develop test automation, analyze results, and help ensure reliable performance in real-world operating environments. 

 

What You Will Do : 

• Execute functional bring-up and system integration on subsystem and system benches. 

• Evaluate system interactions across compute platforms, ECUs, sensors, and vehicle software. 

• Execute functional, performance, and validation tests using simulation, HIL, SIL, benches, and on-road fleets. 

• Develop Python-based automation and supporting tools to improve testing efficiency and accelerate development cycles. 

• Analyze test data, document results, consolidate findings, and support root-cause investigations. 

• Support the creation of datasets, scenario libraries, and automated test pipelines for HIL and SIL environments. 

• Identify problem statements, outline effective solutions, and account for tradeoffs and edge cases. 

• Participate in technical discussions, test planning, design reviews, and cross-functional problem-solving. 

• Collaborate with software, hardware, systems, safety, and vehicle engineering teams to ensure seamless system integration. 

• Communicate test results, technical findings, and recommendations clearly 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, electrical engineering, computer 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. 

• Experience programming in C++, Python, or another object-oriented language. 

• Strong interest in working with hardware, embedded systems, system integration, automated testing, or related areas. 

• Strong problem-solving, analytical, written, and verbal communication skills. 

• Ability to work collaboratively across software, hardware, systems, test, and safety teams. 

• 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. 

 

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. 

• Hands-on experience building, testing, debugging, or integrating hardware and software systems. 

• Familiarity with communication protocols such as CAN, LIN, or Ethernet. 

• Coursework or project experience involving Python, C/C++, embedded microcontrollers, or test automation. 

• Basic understanding of embedded Linux, real-time systems, ECUs, sensors, or vehicle networks. 

• Experience with simulation, hardware-in-the-loop, software-in-the-loop, test benches, or automated validation pipelines. 

• Experience analyzing test data and communicating technical findings or root-cause investigations. 

• Familiarity with common autonomous vehicle sensors, such as cameras, lidar, radar, or IMUs. 

• 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 Warren, MI office three times per week, at minimum. 

GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2027 Student Program - to help facilitate administration of relocation benefits, please apply using the permanent address you would move from. .







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