2027 Summer Intern – Machine Learning Intern, Autonomous Vehicles: Software Validation (Master's)

Job Description

About the Team:

The Autonomous Vehicle (AV) organization is dedicated to advancing the development of autonomous vehicles through cutting-edge simulation technologies and novel iterative development processes. The Software Validation team focuses on unlocking software launches and continuous release decisions via novel simulation V&V methodologies and targeted vehicle testing. Our collaborative environment fosters innovation and excellence, allowing us to push the boundaries of what is possible in autonomous vehicles systems engineering.

About the Role:

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.

What You’ll Do:

· 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.

Required Qualifications

· Currently enrolled & in the process of obtaining a Master's Degree in Computer Science, Machine Learning, Engineering, or a related technical field.

· Graduating between December 2027 and August 2028.

· Experience coding in Python, SQL, C/C++ or others.

Preferred Qualifications:

· 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, or coding competitions.

· 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.

Compensation:

· The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

· The salary range for this role is $8,700 - $10,300 per month. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

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.

What you’ll get from us (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

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.