Systems Research Engineer Intern - GPU Programming (Summer 2027)
About the role
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.
Responsibilities
- 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
Requirements
- 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
Benefits
We offer competitive compensation, housing stipends, and other competitive benefits.
Pay
The estimated US hourly rate for this role is $58 to $70 an hour. Hourly rates are determined by location, level and role; individual compensation will be determined by experience, skills, and job-related knowledge.
Schedule
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 either May 17th to August 6th or June 14th to September 3rd.