NVIDIA
As part of NVIDIA(https://himalayas.app/companies/nvidia)’s Analytics and Data Intelligence (ADI) group, this team develops “libcudf”—the open-source CUDA C++ library that accelerates database and DataFrame operations. With flexible I/O, blazing-fast merging, aggregating, and filtering, our library serves diverse domains, including business intelligence, genomics, LLM training, and more. We use the latest tools in modern C++ and CUDA to produce software with elegant design, broad feature coverage, and best-in-class performance.
The team is looking for an outstanding engineer and/or scientist to apply their parallel programming skills to accelerate open-source software libraries for GPU-based data processing. In this position, you will drive speed-of-light performance in structured data processing, spanning hardware from single workstations to multi-node GPU supercomputers. In addition, you will be building the computational core for DataFrame and database accelerators—highly optimized C++ and CUDA libraries that leverage the parallel nature of GPUs to accelerate operations from data loading and parsing, joins, aggregations, and more. Come bring your inspiration and problem-solving skills to our open-source software suite, and you can be our next major contributor!
What you’ll be doing:
Own development for “UcxExchange” in Velox (30%)
+ GPU-to-GPU communication in Presto: + Drive the feature roadmap, improve performance, and ensure correctness Optimize multi-node performance for analytical queries with Presto GPU (30%)
+ Targeting both on-prem clusters and public cloud servers Lead projects of interest in Presto, Velox, cuDF (40%)
+ Such as operator completeness, GPU memory oversubscription, efficient CPU fallback + Plus your ideas
What we need to see:
8+ years of experience in Computer Science or Software Engineering MS degree or PhD in computer science, engineering, or a related field, or equivalent experience Strong Modern C++ programming skills You care deeply about robu…
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