2027 Intern - AI/ML Engineer - Capacity & Performance Engineering, Autonomous Vehicles

General Motors Corporation; Sunnyvale (CA); Hybrid; USD 107,000 - 132,000; Full time

Benefits offered by this job

Hybrid work arrangement

Stipend for eligible students

Job summary

General Motors Corporation in Sunnyvale, California is seeking a 2027 Intern - AI/ML Engineer for Capacity & Performance Engineering to support capacity intelligence work for autonomous vehicles. This hybrid internship reports to a team focused on compute, networking, storage, and AI infrastructure.

You will develop scalable infrastructure using Java/C++/Python, SQL/BigQuery, and tools like Spark, Ray, Kubernetes, and Slurm while gaining hands-on experience with model training, simulation, and

Qualifications

• Currently enrolled in a full-time degree program pursuing a Bachelor's or Master's in computer science or a related technical field.
• Experience in systems software or algorithms.
• Proficiency in Java, C++, and Python; comfortable with SQL/BigQuery.
• Strong communication and cross-functional teamwork.

Responsibilities

• Develop scalable infrastructure, tools and insights to support capacity intelligence workflows.
• Code deliverables in collaboration with the engineering team.
• Contribute to capacity models, data generation and performance optimization.

Skills

Java

C++

Python

SQL

BigQuery

Data structures

Communication

Team collaboration

Object-oriented programming

Education

Bachelor's or Master's in CS/related field

Tools

Spark

Ray

Kubernetes

Slurm

Job description

## 2027 Intern - AI/ML Engineer - Capacity & Performance Engineering, Autonomous VehiclesApply: Hybrid: Sunnyvale, California, United States of America: Full time: Posted Today: JR-202622406**Job Description****Work Arrangement:**Hybrid: This internship is categorized as a hybrid. The selected intern is expected to report to the office up to three times per week or as determined by the team. **Location:**Sunnyvale, California **About the Team:**The AV / AI Capacity & Performance Engineering team helps provide the right compute, networking, storage, and AI infrastructure to support AI and ML innovation supporting a wide range of use cases across teams such as Embodied AI, Simulation, Data Science, and more. The team builds capacity models, improves cloud efficiency, supports vendor planning, and develops tooling that makes capacity, demand, utilization, reliability, and cost visible to engineering stakeholders. Our Capacity Intelligence system is being developed as the team’s operational interface and single point of truth for capacity intake, cloud spending, budget pacing, quota and queue analysis, egress forecasting, and related capacity insights. It is being expanded to incorporate new cloud providers and provide advanced modeling capabilities. Our tools and systems empower GM to tackle the complexities of autonomous driving technology and expedite our path to commercialization. **About the Role:** As an intern, you will help develop and optimize our capacity intelligence system with a focus on integrating new capabilities. **What You’ll Do:** • Develop scalable infrastructure, tools and insights to support Model Training, Simulation, CI Build and Data Generation insights with the capacity intelligence program. • Code deliverables in tandem with the engineering team.• 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 Bachelor's or 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). Experience coding in Python.• Experience with SQL, BigQuery• Strong communication skills with experience collaborating across cross-functional teams.• Able to work full-time, 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).• Demonstrated creativity and quick problem-solving capabilities.• Research and/or work experience in machine learning infrastructure.• Experience with distributed systems (e.g., Spark, Ray, Kubernetes, Slurm).• Experience in scheduling algorithms, orchestration or compute.• Intent to return to degree-program after internship.• Graduating between December 2027 and August 2028. **Compensation:**• The monthly salary range for this role is $9,600 - $11,800 per month.• GM will provide a one-time lump sum taxable stipend payment to eligiblestudents selected for the 2027 Student Program.