NVIDIA’s data science and AI platforms, like the RAPIDS open-source suite of analytics libraries, power modern data science and engineering across the world. The team builds or integrates dozens of tools, collaborating with both commercial partners and the open-source community. We are looking for an outstanding senior engineer to play a key role in packaging, automation, and related infrastructure.

This role is progressive for an enthusiastic generalist who knows or wants to learn technologies ranging from the guts of Python wheels, Conda packages, and CUDA/C++ libraries on up the stack through Docker and Github Actions. You will have the opportunity to contribute to both open-source and enterprise platforms trusted by our largest partners. You will be able to improve deployment on next-generation, pre-release NVIDIA hardware and software platforms and contribute back to help major GPU-accelerated packages fit in well with the open-source Python ecosystem.

What you’ll be doing:

• Developing and modernizing packages, such as streamlined Python wheels, for RAPIDS data science libraries

• Designing and maintaining container build processes

• Digging into deployment needs of sophisticated new hardware and software platforms

• Debugging

• Automating critical build pipelines

What we need to see:

• 6+ years of proven experience in software development, build, and/or related devops

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field (or equivalent experience)

• Experience building Python packages, such as wheels, conda packages, etc.

• An understanding of container technology, such as Docker

• A love of automating all major processes and knowledge of at least one build automation platform, like Github Actions, Jenkins, etc.

• Strong overall coding skills, especially in Python

Ways to stand out from the crowd:

• Deep understanding of linking, loading, and Linux binary formats

• C++ experience as well as knowledge of CUDA or similar parallel programming paradigms

• Experience with C/C++ extensions for Python, including tools like Cython or PyBind11

• CMake usage or development experience

• Familiarity with GPU platforms and deployments with a passion for making end user experiences easier and more reliable!

With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and talented people in the world working with us and our engineering teams are growing fast in some of the most impactful fields of our generation.

The base salary range is 180,000 USD - 339,250 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.