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.

We’re growing the team developing core libraries within RAPIDS. In this role, you will develop, benchmark, and architect backend libraries and frontend APIs. This is a great chance to take advantage of your fundamental computer science as well as more practical topics such as the PyData Stack, CUDA, C++, and Python programming skills. You’ll work closely with the RAPIDS team of stellar engineers building highly-optimized CUDA libraries.

What you'll be doing:

• 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

What we need to see:

• 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

Ways to stand out from the crowd:

• 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 is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of accelerated computing.

The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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