Parallel Computing Jobs

NVIDIA's Architecture Research Group is seeking a PhD intern to contribute to defining the future of GPU and data-center computing. This role involves exploring foundational research questions in areas such as GPU microarchitecture, memory systems, large-scale data-center hardware, and emerging accelerators, with a focus on the architectural implications of AI and scientific computing workloads. The intern will apply knowledge of computer architecture, parallel computing, compilers, and runtime systems to identify and develop new hardware and hardware-software co-design opportunities, working alongside researchers and product architects to formulate research questions, evaluate concepts, and build necessary models and simulators.

$0k - $0k

Together AI

As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. You will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems, and contribute to the co-design of efficient GPU architectures and programming models. 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.

$200k - $300k

Together AI

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. You will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems, and contribute to the co-design of efficient GPU architectures and programming models. 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.

$121k - $146k

Together AI

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. You will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems, and contribute to the co-design of efficient GPU architectures and programming models. 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.