About the job
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. 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
Qualifications
Minimum
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
Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences
Preferred
No preferred qualifications listed.