Offer summary

Qualifications:

PhD or MSc in Computational Science, Computer Science, Applied Math, or related field., At least 5 years of experience in developing and optimizing high-performance parallel numerical applications with GPU acceleration using CUDA., Strong proficiency in C/C++ programming and software design., Excellent collaboration, communication, and documentation skills..

Key responsibilities:

Develop scalable library software for numerical methods using modern tools and languages.

Perform performance tuning, optimization, and benchmarking of algorithms on various architectures.

Collaborate with product management and partners to define feature and performance requirements.

Provide technical leadership and guidance to library engineering teams.

Job description

Join our multidisciplinary team and help build and improve GPU and CPU accelerated software libraries. Projects like nvComp, NPP, nvJPEG, nvJPEG2000, nvTIFF, nvImageCodec or DALI are used in all kinds of processing workflows and support NVIDIA's vision and growth.

Starting from powering AI, data analytics, image processing, computer vision, and scientific simulations for leading commercial and academic organizations worldwide. In this role, you will design, develop, and optimize pioneering algorithms. Ideal candidates will have experience with accelerated computing and a passion for advancing the state-of-the-art in various computing domains. If this sounds exciting, we would love to meet you!

What you’ll be doing:

developing scalable library software using modern tools and languages for various numerical method
performance tuning, optimization, and benchmarking of algorithms on various architectures.
working closely with product management and other internal and external partners to understand feature and performance requirements and contribute to the technical roadmaps of libraries,
providing technical leadership and guidance to library engineers working with you,
find opportunities to improve library performance and abstractions that allow to re-architect code for reduced maintenance cost.

What we need to see:

PhD or MSc’s degree in Computational Science, Computer Science, Applied Math, or related science or engineering field of study is preferred (or equivalent experience).
5+ years experience developing, debugging, and optimizing high-performance parallel numerical applications on modern computing platforms, with GPU acceleration using CUDA
Excellent C/C++ programming and software design skills
Proven experience in leading and completing software development projects.
Excellent collaboration, communication, and documentation habits.

Ways to stand out from the crowd:

Good knowledge of CPU and/or GPU hardware architecture,
Experience with adopting and advancing, software development practices such as CI/CD systems and project management tools such as JIRA,
Experience with working in a globally distributed organization,
Advanced skills in debugging, profiling, and testing for accuracy and performance,
A scripting language, preferably Python.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all.

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