About the role#
As a Systems Research Engineer Intern, you will focus on developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. You will work alongside modeling and algorithm teams to co-design GPU kernels and model architectures, aiming to enhance the performance and efficiency of AI systems. This role involves contributing to the co-design of GPU architectures and programming models while staying current with advancements in the field.
What you'll do#
- Optimize and fine-tune GPU code to improve performance and scalability.
- Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems.
- Monitor and implement the latest advancements in GPU programming techniques and technologies.
What you'll need#
- Strong background in GPU programming and parallel computing, specifically CUDA and/or Triton.
- Knowledge of ML/AI applications and models.
- Experience with performance profiling and optimization tools for GPU programming.
- Excellent problem-solving and analytical skills.
- Pursuing a degree in Computer Science, Computer Engineering, Electrical Engineering, or Data Science.
Location & details#
- Location: San Francisco, California.
- Term: Fall 2026 (September 14th to December 18th).
- Duration: 12 to 16 weeks.
- Modality: On-site.
- Compensation: $58 to $63 per hour, including housing stipends and benefits.
