2026 Summer Intern – Machine Learning Systems Engineer – Autonomous Driving (Master's Degree)
General Motors
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San Francisco, CA
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0
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Not Applicable
Posted May 3, 2026
Job link
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Responsibilities
Commitments
Responsibilities
- Develop scalable infrastructure and tools to support model training, regression, and rules-based models, operations, and inference.
- Suggest, collect and synthesize requirements and create effective feature roadmap.
- Code deliverables in tandem with the engineering team.
- Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
- Perform specific responsibilities which vary by team.
Commitments
Work Arrangement:
Hybrid: This internship is categorized as hybrid.
The selected intern is expected to report to the office up to three times per week or as determined by the team.
To help facilitate administration of the relocation stipend if you are selected, please apply using the permanent address you would move from.
Location:
San Francisco, California
Able to work fulltime, 40 hours per week.
Intent to return to degree-program after the completion of the internship.
Graduating between December 2026 and August 2027.
GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2026 Student Program.
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.
If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 800-865-7580.
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Requirements
- Currently enrolled in a full-time, degree-seeking program and in the process of obtaining a Master's degree in computer science or a related technical field.
- Experience in systems software or algorithms.
- Experience with modern object-oriented programming languages (e.g., Java, C++, Python).
- Strong communication skills with experience collaborating across cross-functional teams.
- Able to work fulltime, 40 hours per week.
- Intent to return to degree-program after the completion of the internship.
- Graduating between December 2026 and August 2027.
Preferred Skills
- Demonstrated software engineer experience via an internship, work experience, coding competitions.
- Familiarity with AI –assisted engineering tools (e.g., for code generation, model analysis, or experiment planning) to enhance productivity and understanding of ML systems.
- Demonstrated creativity and quick problem-solving capabilities.
- Research and/or work experience in a relevant field, such as machine learning, deep learning, reinforcement learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, or computer vision.
- Experience with distributed systems (e.g., Spark, Ray, Kubernetes, Slurm).
- Experience in CUDA, OpenCL, Triton or other accelerator programming language.
Education
- (Not required) – Currently enrolled in a full-time, degree-seeking program and in the process of obtaining a Master's degree in computer science or a related technical field.
- (Not required) – Research and/or work experience in a relevant field, such as machine learning, deep learning, reinforcement learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, or computer vision.
- (Not required) – Intent to return to degree-program after the completion of the internship.
- (Not required) – Graduating between December 2026 and August 2027.
Job Description
About the Team:
We are building a state-of-the-art AI training platform in close collaboration with model teams to deliver Autonomous car milestones, maximizing model flop utilization and iteration speed, and enhancing inference systems. We are augmenting training, data processing, evaluation and the deployment loop with a data flywheel to validate performance and continuously improve Autonomous driving and Active Safety. We accelerate compute performance through architectural changes and low-level optimizations, informed by advanced Carbench/HIL platforms, AI tooling and workflows and instrumentation built in-house. We streamline compiler/build and modelbench performance; enhance data processing, preprocessing, and batch inference; and improve monitoring and availability to increase velocity and quality.
Work Arrangement:
Hybrid: This internship is categorized as hybrid. The selected intern is expected to report to the office up to three times per week or as determined by the team.
To help facilitate administration of the relocation stipend if you are selected, please apply using the permanent address you would move from.
Location:
San Francisco, California
Sunnyvale, California
Mountain View, California
Seattle, Washington
About the Role:
As an intern, you will help develop and optimize our AI training platform by improving data processing pipelines, accelerating model training and inference workflows, and/ or enhancing testing infrastructure like Carbench/HIL. You will support tool development, instrumentation, and system monitoring to boost reliability, reduce latency, and increase iteration speed for advancing autonomous driving performance.
What You’ll Do:
Develop scalable infrastructure and tools to support model training, regression, and rules-based models, operations, and inference.
Suggest, collect and synthesize requirements and create effective feature roadmap.
Code deliverables in tandem with the engineering team.
Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
Perform specific responsibilities which vary by team.
Required Qualifications:
Currently enrolled in a full-time, degree-seeking program and in the process of obtaining a Master's degree in computer science or a related technical field.
Experience in systems software or algorithms.
Experience with modern object-oriented programming languages (e.g., Java, C++, Python).
Strong communication skills with experience collaborating across cross-functional teams.
Able to work fulltime, 40 hours per week.
Preferred Qualifications
Demonstrated software engineer experience via an internship, work experience, coding competitions.
Familiarity with AI –assisted engineering tools (e.g., for code generation, model analysis, or experiment planning) to enhance productivity and understanding of ML systems.
Demonstrated creativity and quick problem-solving capabilities.
Research and/or work experience in a relevant field, such as machine learning, deep learning, reinforcement learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, or computer vision.
Experience with distributed systems (e.g., Spark, Ray, Kubernetes, Slurm).
Experience in CUDA, OpenCL, Triton or other accelerator programming language.
Intent to return to degree-program after the completion of the internship.
Graduating between December 2026 and August 2027.
Compensation:
The monthly salary range for this role is $ 7,300 - $10,600 per month.
GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2026 Student Program.
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 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.
About the Team:
We are building a state-of-the-art AI training platform in close collaboration with model teams to deliver Autonomous car milestones, maximizing model flop utilization and iteration speed, and enhancing inference systems. We are augmenting training, data processing, evaluation and the deployment loop with a data flywheel to validate performance and continuously improve Autonomous driving and Active Safety. We accelerate compute performance through architectural changes and low-level optimizations, informed by advanced Carbench/HIL platforms, AI tooling and workflows and instrumentation built in-house. We streamline compiler/build and modelbench performance; enhance data processing, preprocessing, and batch inference; and improve monitoring and availability to increase velocity and quality.
Work Arrangement:
Hybrid: This internship is categorized as hybrid. The selected intern is expected to report to the office up to three times per week or as determined by the team.
To help facilitate administration of the relocation stipend if you are selected, please apply using the permanent address you would move from.
Location:
San Francisco, California
Sunnyvale, California
Mountain View, California
Seattle, Washington
About the Role:
As an intern, you will help develop and optimize our AI training platform by improving data processing pipelines, accelerating model training and inference workflows, and/ or enhancing testing infrastructure like Carbench/HIL. You will support tool development, instrumentation, and system monitoring to boost reliability, reduce latency, and increase iteration speed for advancing autonomous driving performance.
What You’ll Do:
Develop scalable infrastructure and tools to support model training, regression, and rules-based models, operations, and inference.
Suggest, collect and synthesize requirements and create effective feature roadmap.
Code deliverables in tandem with the engineering team.
Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
Perform specific responsibilities which vary by team.
Required Qualifications:
Currently enrolled in a full-time, degree-seeking program and in the process of obtaining a Master's degree in computer science or a related technical field.
Experience in systems software or algorithms.
Experience with modern object-oriented programming languages (e.g., Java, C++, Python).
Strong communication skills with experience collaborating across cross-functional teams.
Able to work fulltime, 40 hours per week.
Preferred Qualifications
Demonstrated software engineer experience via an internship, work experience, coding competitions.
Familiarity with AI –assisted engineering tools (e.g., for code generation, model analysis, or experiment planning) to enhance productivity and understanding of ML systems.
Demonstrated creativity and quick problem-solving capabilities.
Research and/or work experience in a relevant field, such as machine learning, deep learning, reinforcement learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, or computer vision.
Experience with distributed systems (e.g., Spark, Ray, Kubernetes, Slurm).
Experience in CUDA, OpenCL, Triton or other accelerator programming language.
Intent to return to degree-program after the completion of the internship.
Graduating between December 2026 and August 2027.
Compensation:
The monthly salary range for this role is $ 7,300 - $10,600 per month.
GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2026 Student Program.
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 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.