The NVIDIA Architecture Modelling group is looking for architects and software developers to join our various architecture efforts. A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields, delivering the highest performance in the world for high-performance computing. We are constantly looking for ways to improve our GPU architecture and maintain our leadership. In this position, you will be working with other world-class architects on modeling, analysis and validation of chip architectures and features that advance the state of art in performance and efficiency.
What you'll be doing:
- Modeling and analysis of graphics and / or SOC algorithms and features
- Work in a team to document, design, develop tools to analyze and simulate, validate, and verify models
- Develop tests, test plans, and testing infrastructure for new architectures/features
- Code coverage analysis and reporting
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What we need to see:
- Bachelors Degree (or equivalent experience) in a relevant discipline (Computer Science, Electrical Engineering or Computer Engineering) with 8+ years of relevant work experience or MS with 3+ years of experience or PhD with 2+ years of experience
- Strong programming ability: C++, C along with a good understanding of build systems (CMAKE, make) , toolchains (GCC, MSVC) and libraries (STL, BOOST)
- Computer Architecture background with experience in modeling with SystemC & TLM preferred
- Familiarity with Docker, Jenkins, Python, Perl
- Excellent communication and interpersonal skills and ability to work in a distributed team environment
With competitive salaries and a generous benefits package, 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. Are you a creative and autonomous engineer with a real passion for computer architecture and technology? If so, we want to hear from you! Come join our Architecture team and help us craft the fastest and most power efficient GPUs and SoCs in their segment.