Senior Architect, GPU and SoC Modelling at NVIDIA

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

14 Feb, 26

Salary

0.0

Posted On

16 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

C++, C, Computer Architecture, Performance Modeling, SystemC, Docker, Jenkins, Python, Perl, Build Systems, Toolchains, Libraries, Communication Skills, Interpersonal Skills, Mentoring, AI Tools

Industry

Computer Hardware Manufacturing

Description

NVIDIA has continuously reinvented itself. Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel. 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 matrixed environment, across the different modelling teams, to document, design, develop tools to analyze and simulate, validate, and verify models Familiarize with the different models (functional and performance) that are used at Nvidia and help with feature implementation as required. Develop tests, test plans, and testing infrastructure for new architectures/features. Mentor younger engineers and help sustain good coding practices. Learn about newer modelling techniques and frameworks, evaluate the best solution for our needs and work with your manager to drive the change Help develop AI based tools to increase efficiency. What we need to see: Bachelors Degree (or equivalent experience) in a relevant discipline (Computer Science, Electrical Engineering or Computer Engineering) 8+ years of relevant work experience or MS with 5+ 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 performance modeling with C++ and SystemC preferred Familiarity with Docker, Jenkins, Python, Perl Excellent communication and interpersonal skills and ability to work in a distributed team environment. NVIDIA’s invention of the GPU 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. Today, we are increasingly known as “the AI computing company”. 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. Do you love the challenge of crafting the highest-performance silicon GPUs and SoCs possible? If so, we want to hear from you! Come, join our Architecture Simulation and Modelling team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. #LI-Hybrid NVIDIA is the world leader in accelerated computing. NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. Learn more about NVIDIA.

Responsibilities

You will be involved in modeling, analysis, and validation of chip architectures and features. This role requires collaboration across different modeling teams to develop tools for analysis and simulation.