Systems Research Engineer Intern - GPU Programming (Winter 2027)

Together AI · Research

Where: San Francisco
Posted: Sep 18

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.

What you'd do

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

What they want

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

About Together AI · Research

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own.