Verification Engineer, Performance

7 months ago


Bengaluru, India NVIDIA Full time

We are now looking to hire strong performance verification engineers with a sharp understanding of CPU and memory architecture. NVIDIA makes some of the fastest CPUs in the world and is solving problems, with its vast arsenal of CPUs, GPUs and SW, in areas such as High-performance computing, Automated driving, Medical imaging and much more We are seeking highly motivated engineers to join this dynamic and innovative team that owns performance alignment of CPUs and CPU fabrics made by NVIDIA Do you want to be part of the team that explores and defines the next generation of CPUs?

What will you be doing:

  • Responsibilities will include development of test plans and strategies, develop simulation environments, system bring-up, validation, and automation to deliver best-in-class CPUs.

  • Develop and maintain CPU simulator infrastructure, hardware CPU test and performance infrastructure.

  • Analyze and validate CPU and fabric performance, helping to understand current, and guide the development of future CPU products.

  • Definition and development of tool chain and workflows that enables the full system performance alignment.

  • Silicon based competitive analysis of NVIDIA CPUs.

 

What we need to see:

  • Strong understanding of computer system architecture and operating system fundamentals.

  • 2+ years of experience in the field of Computer architecture / CPU Architecture / Performance analysis / workload analysis

  • Master's or Bachelor's degree in EE/CS or related field

  • Hands-on experience with HDLs such as Verilog / System Verilog.

  • Knowledge of verification methodologies and tools for IP and SoC level verification.

  • Experience with System Verilog, C/C++, Python languages and relevant frameworks.

  • Background with debug on Silicon.

 

Ways to stand out from the crowd:

  • Detailed knowledge of the ARM and/or x-86 architecture.

  • Prior experience with performance analysis of CPUs.

  • Experience with analysis and characterization of CPU workloads.



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