2027 Intern - AI/ML Engineer - Capacity & Performance Engineering, Autonomous Vehicles
About The Position
As an intern, you will help develop and optimize our capacity intelligence system with a focus on integrating new capabilities. 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.
Requirements
- 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.
Nice To Haves
- 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.
Responsibilities
- 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.
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
- GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2027 Student Program.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
