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Senior Library Acceleration Engineer, RAPIDS

NVIDIA is the world leader in accelerated computing, pioneering accelerated computing to tackle challenges no one else can solve.
New York, NY, USAAtlanta, GA, USACharlotte, NC, USA
$148,000 - $276,000
Backend
Senior Software Engineer
Remote
5,000+ Employees
5+ years of experience
AI · Enterprise SaaS
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Description For Senior Library Acceleration Engineer, RAPIDS

NVIDIA is hiring Systems Software Engineers to work on RAPIDS, a suite of open-source software libraries that accelerates end-to-end data science and analytics pipelines on GPUs. RAPIDS relies on NVIDIA CUDA for low-level compute optimization but exposes that high-performance GPU compute through user-friendly Python interfaces.

In this role, you will develop, benchmark, and architect backend libraries and frontend APIs. You'll work closely with the RAPIDS team of stellar engineers building highly-optimized CUDA libraries.

Responsibilities:

  • Analyze, design, and implement optimized GPU algorithms for data analytics and machine learning
  • Expand and improve integration of RAPIDS into relevant high-level frameworks
  • Drive performance analysis, benchmarking, and trouble-shooting of associated libraries
  • Collaborate with a multi-functional team to understand requirements and implement or improve solutions

Requirements:

  • MS or PhD in Computer Science, Computer Engineering or Electrical Engineering or related field in Deep Learning, Machine Learning, and Computer Vision or equivalent experience
  • 5+ years of proven experience in Computer Science, Artificial Intelligence, Applied Math, or related field
  • Expert level knowledge in building and maintaining Python interfaces to lower level libraries, preferably in C++ (CUDA a bonus)
  • Strong analytical problem-solving skills, algorithms and mathematics fundamentals
  • Excellent software development skills: programming, debugging, performance analysis, and test design
  • Good communication and documentation habits
  • Ability to work independently and manage your own development efforts
  • A passion for thoughtful benchmarking

Nice to have:

  • Experience developing distributed algorithms and running on distributed systems: HPC, Cloud, etc
  • Background with debugging multi-language and multi-hardware systems
  • Experience with PyData: NumPy, Pandas, Scikit-Learn, Dask, Xarray, Zarr
  • Prior work on open-source projects
  • GPU programming knowledge is a plus, but if you don't have it, we're happy to teach you

NVIDIA offers a competitive salary package and benefits, and is widely considered to be one of the technology world's most desirable employers. Join us in leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization.

Last updated 7 months ago

Responsibilities For Senior Library Acceleration Engineer, RAPIDS

  • Analyze, design, and implement optimized GPU algorithms for data analytics and machine learning
  • Expand and improve integration of RAPIDS into relevant high-level frameworks
  • Drive performance analysis, benchmarking, and trouble-shooting of associated libraries
  • Collaborate with a multi-functional team to understand requirements and implement or improve solutions

Requirements For Senior Library Acceleration Engineer, RAPIDS

Python
  • MS or PhD in Computer Science, Computer Engineering or Electrical Engineering or related field
  • 5+ years of proven experience in Computer Science, AI, Applied Math, or related field
  • Expert level knowledge in building Python interfaces to lower level libraries
  • Strong analytical problem-solving skills
  • Excellent software development skills
  • Good communication and documentation habits
  • Ability to work independently
  • Passion for thoughtful benchmarking

Benefits For Senior Library Acceleration Engineer, RAPIDS

Equity
Medical Insurance
  • Equity
  • Medical Insurance

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