CPU Verification Infrastructure Tools Architect

Posted 2 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The role involves developing test frameworks and tools for RTL and silicon that interact with various SOC components. Responsibilities include creating infrastructure for simulations, understanding Tegra system architecture, and ensuring high-quality software that supports Design and Verification teams.
Summary Generated by Built In

We are looking for a Hardware and Software Developer. The role is multifaceted - SoCV testbench Infrastructure, Bare-metal boot, Silicon Bringup Tools and CPU/SOC/GPU test frameworks. It involves a detailed understanding of the NVIDIA CPU, GPU, SOC system and boot architectures. The tools and technologies are complex and involve code that coordinates many IPs in the overall SOC. A key part of NVIDIA's strength is our development tools and environments that enable our incredible pace of delivering new technology to the market. We are looking for a creative and hardworking engineer who is passionate about joining a dynamic & agile SoCV/Emulation Infrastructure and test-frameworks team.

What you will be doing:

  • The work includes building tools, infrastructure, and test frameworks used in RTL-simulations, c-simulations, Emulation, FPGA, and on Silicon.

  • You will understand Tegra system architecture, with a focus on all IPs in the SOC that are involved in boot and security features.

  • The tools that you build give Design and Verification teams the ability to access registers/memory/DMA engines and other features in their unit. The tools also enable test re-use across multiple platforms (RTL, models, Emulation, and Silicon). The gamut of tools is wide and you also develop features used for Silicon bring up (example: FUSE, ATE, Security, Flash/DMA, Board I2Cs, USB debug devices among others). We strive for the highest quality of test frameworks and tools that we deliver from this team.

  • You would assess and build C-model or RTL-simulation capability that allows us to simulate the features before Silicon arrival in a pre-silicon environment.

What we need to see:

  • BS or MS in Computer Science or Electronics Engineering or equivalent experience with 5+ years of experience

  • Strong programmer who is proficient with C, C++, Python.

  • Understanding of SOC and System Architecture.

  • Understanding of How the SOC Devices like DMA, interrupt-engines, CPU, boot-devices, MMU/IOMMU function.

  • Operating System and Device-Driver concepts and ability to write no-OS test frameworks - i.e tests that run directly on the bare-metal SOC.

  • A good programmer takes pride in building scalable and maintainable software.

  • Understanding Hardware and/or Software development life cycle.

Way to stand out from the crowd:

  • Previous experience handling Silicon Bringup and in enabling Emulation/FPGA related test frameworks.

  • Exposure to Testbench architectures (C++ testbenches, SV/UVM based testbenches).

  • Verilog and System Verilog coding skills are a plus.

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our elite engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you! We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Top Skills

C
C++
Python
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

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. Today, NVIDIA is increasingly known as “the AI computing company.”

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