Description About the team

We focus on developing high-performance GPU kernels and custom libraries that power state-of-the-art ML models' on-vehicle inference. Our charter is to make core AI workloads faster, more reliable, and easier to maintain and deploy. That includes building custom operators when vendor libraries fall short, integrating those kernels into our ML runtime stack, and consulting on performance and CUDA debugging across the AV software stack. We collaborate closely with AI Solutions, AI Compilers, AI Architecture, and AI Tooling to ensure models can be deployed efficiently to the car while meeting strict latency and reliability targets.

About the role

As an AI Kernels intern, you'll work alongside experienced kernel, compiler, and performance engineers on real production problems-profiling GPU workloads, experimenting with new kernel implementations, and strengthening the performance and robustness of the AI stack behind GM's next-generation autonomous and assisted driving features. You'll design, implement, and benchmark CUDA kernels and supporting infrastructure, contributing to the GPU kernels and custom libraries that improve performance, reliability, and developer experience across our ML stack.

What You'll Do:

• Design and optimize GPU kernels and supporting libraries for core model operations used in on-vehicle inference.

  • Build and improve tooling and infrastructure that make it easier to profile, debug, and validate CUDA kernels and accelerator-backed code.

  • Help define and refine kernel requirements and priorities by working with partners in AI Solutions, Compilers, and Architecture, and turning them into concrete tasks and project plans.

  • Implement, benchmark, and iterate on CUDA-based solutions to get the most out of modern GPU hardware for real production workloads.

  • Take on team-specific projects, which may include performance investigations, reliability improvements, or prototype explorations depending on current priorities.

Required Qualifications

• Currently enrolled in a PhD program in Computer Science, Computer Engineering, Electrical Engineering, Applied Math / Computational Science or a related STEM field.

• Availability to work full-time (40 hours per week) during the internship period.

• Demonstrated coursework, research, or projects in GPU programming, parallel computing, high-performance computing (HPC), machine learning systems, or computer architecture.

• Strong programming skills in C++

Preferred Qualifications

• Experience with CUDA/CUTLASS/Cu Te or other accelerator programming framework, such as OpenCL.

• Familiarity with GPU performance profiling tools (e.g., Nsight Systems, Nsight Compute, nvprof).

• Experience with mixed-precision computation (FP16 / INT8) and performance-accuracy tradeoffs.

• Knowledge of GPU-accelerated libraries (e.g., cub, cuBLAS, cuDNN, TensorRT) and when to use custom kernels vs. library calls.

• Background in parallel algorithms, numerical methods, or high-performance computing (HPC).

• Prior research, publications, or coursework involving GPU acceleration or systems-level optimization.

Location:

Sunnyvale, CA

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.

Compensation:

• The monthly salary range for this role is $11,100 - $13,100

  • GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2026 Student Program.

To help facilitate administration of the relocation stipend if you are selected, 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.

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