NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. We're looking to grow our company, and form teams with the most inquisitive people in the world. Join us at the forefront of technological advancement.
We are looking for an experienced software professional to lead/extend our work on the Legion and Realm runtimes for large-scale distributed GPU computing, unlocking the power of distributed GPU computing by developing foundational software that supports many key products spanning the gamut of data analytics, deep learning, HPC and professional graphics running on hardware ranging from supercomputers to the cloud.
What you'll be doing:
As a member of our team, you will use your design abilities, coding expertise, and creativity to develop and improve the functionality and performance of runtime systems that underlay the foundation of distributed GPU computing at NVIDIA.
Architect, prioritize, and develop new features
Analyze and improve the performance for key applications
Write effective, maintainable, and well-tested code for production use
What we need to see:
BS, MS or PhD degree in Computer Science, Electrical Engineering or related field (or equivalent experience)
5+ years of relevant industry experience or equivalent academic experience after BS
Strong C/C++ and CUDA programming skills
Background in high performance computing and performance critical applications
Experience implementing, tuning, and debugging runtimes and/or distributed systems for supercomputers or the cloud
Good written communication, teamwork, and presentation skills
Ways to stand out from the crowd:
Background with tasking or asynchronous runtimes, especially data-centric initiatives such as Legion
Dexterity with compilers and static/dynamic alias analysis techniques
Experience using Python for HPC
Knowledge of high performance spatial data structures and algorithms used in accelerating point and ray queries
Development of domain specific libraries/languages for high performance computing
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Last updated: 23 hours ago
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