Systems Research Engineer Intern - GPU Programming (Fall 2026)
Remote • San Francisco
Posted 1mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. You will co-design GPU kernels and model architecture with the modeling and algorithm team to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation.
Responsibilities
- Optimize and fine-tune GPU code for performance and scalability.
- Collaborate with cross-functional teams to integrate GPU-accelerated solutions.
- Stay updated on the latest GPU programming techniques and technologies.
Requirements
- Strong background in GPU programming and parallel computing (e.g., CUDA, Triton).
- Knowledge of ML/AI applications and models.
- Familiarity with GPU programming performance profiling and optimization tools.
- Excellent problem-solving and analytical skills.
Benefits
- Competitive compensation
- Housing stipends
- Other competitive benefits