Systems Research Engineer Intern
Together AI
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. This internship is based on-site at our San Francisco HQ, running through the Winter term from January to April.
Key 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 & Tech Stack
- 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
- Internship Dates: January 4th to April 9th
- Duration: 12 to 14 weeks
- Location: San Francisco HQ (on-site)