Senior Distributed Acceleration Engineer, RAPIDS

NVIDIA is seeking a Senior Distributed Acceleration Engineer to join their RAPIDS team, focusing on open-source software libraries that accelerate data science and analytics pipelines on GPUs. The role involves developing and optimizing multi-GPU solutions, working with CUDA C++ and Python to create high-performance distributed systems. The position offers an opportunity to work with cutting-edge technology in GPU computing and contribute to NVIDIA's mission in accelerated computing.

The ideal candidate will have strong expertise in distributed systems and algorithm optimization, with the ability to work on complex multi-GPU configurations. They will be responsible for implementing and improving distributed GPU algorithms, performance analysis, and integration with various frameworks like Dask, Ray, and Spark.

This is an exciting opportunity to join NVIDIA, a leader in AI and GPU technology, working on groundbreaking developments in artificial intelligence, high-performance computing, and visualization. The company offers competitive compensation, including equity and comprehensive benefits, and fosters a diverse, inclusive work environment.

The role combines technical expertise in distributed systems with the opportunity to work on cutting-edge GPU technology, making it perfect for someone passionate about high-performance computing and data science. You'll be part of a team developing solutions that push the boundaries of what's possible in accelerated computing, working with some of the industry's most talented engineers.