Systems Research Engineer Intern - GPU Programming (Winter 2027)

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. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture 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.

This internship is based on-site at our San Francisco HQ, running through the Winter term from January to April.

• Optimize and fine-tune GPU code to achieve better performance and scalability
• Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems
• Stay up-to-date with the latest advancements in GPU programming techniques and technologies
• Strong background in GPU programming and parallel computing, such as CUDA and/or Triton.
• Knowledge of ML/AI applications and models
• Knowledge of performance profiling and optimization tools for GPU programming
• Excellent problem-solving and analytical skills

Internship Program Details:

Our internship program runs 12 to 14 weeks, giving you the opportunity to work alongside industry-leading engineers and researchers across multiple teams. This cohort's internship dates span January 4th to April 9th.

We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58 to $70 an hour. Our hourly rates are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.