2026 Summer Intern - Software Engineer, Machine Learning Validation (PhD)
About The Position
As a Machine Learning Validation Engineer on the Software Validation team within the AV organization, you will play a critical role in the execution of validation efforts for autonomous vehicle behavior. You will leverage your skillsets to craft guidance on behavioral performance and to design and implement complex V&V strategies. You will work with a team of engineers to define best practices, design and execute innovative analyses to establish performance requirements, drive innovation in testing, and verify the safety and performance of autonomous systems. You will be responsible for shaping the future of evaluation methodologies for AI systems and other ADAS features, architecting solutions that meet the testing needs of AI developers, systems engineers, and safety stakeholders.
Requirements
- Currently enrolled in a Master's program (with at least one year completed) or in the process of obtaining a PhD in Computer Science, Machine Learning, Engineering, or a related technical field.
- Experience coding in Python, SQL, C/C++ or others.
Nice To Haves
- Graduating between December 2026 and August 2027.
- Research and/or work experience in a relevant field, such as machine learning, simulation, AI validation, deep learning, reinforcement learning, data mining, or computer vision.
- Intent to return to degree-program after the completion of the internship.
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or PhD papers.
- Experience in systems software or algorithms.
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences.
- Demonstrated creativity and quick problem solving capabilities.
- Experience with Hadoop/Hbase/Pig or Mapreduce/Sawzall/Bigtable.
Responsibilities
- Enhance AI/ML validation frameworks and tools for autonomous vehicle software systems.
- Design and implement automated testing pipelines for sim-based and real-world validation scenarios using ML.
- Use ML experience to enhance simulated performance metrics.
- Build tools leveraging ML and stats methods to id edge cases, and failure modes in AV.
- Analyze large scale driving data to identify validation gaps and improve testing coverage.
Benefits
- Paid US GM Holidays
- GM Family First Vehicle Discount Program
- Result-based potential for growth within GM
- Intern events to network with company leaders and peers
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Career Level
Intern
Industry
Transportation Equipment Manufacturing
Education Level
Ph.D. or professional degree
Number of Employees
5,001-10,000 employees
