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Location
In office (Bengaluru)
Seniority
Middle · 3+ years exp
Employment
Full-Time
Overview
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NVIDIA is an American technology company founded in 1993 that invented the graphics processing unit and has become the dominant supplier of accelerated computing platforms for artificial intelligence. Its portfolio spans data centre GPUs and systems built on the Hopper and Blackwell architectures, GeForce consumer graphics, automotive and robotics platforms, high-speed networking acquired with Mellanox, and the CUDA software stack that binds the ecosystem together. Headquartered in Santa Clara, California, the company sells to cloud providers, enterprises, research institutions and gamers worldwide and is one of the most valuable listed businesses on the Nasdaq.

NVIDIA is looking for HWQA Engineer who is passionate to drive quality improvements. This essential role will give you an opportunity to collaborate with other test and development teams to build and qualify exceptional products. We value diversity, you will have the opportunity to develop your skillset and build domain expertise (SME) in the areas of SoC Hardware and Software.

What you'll be doing:

  • Design, build and implement test cases and Test plans on Pre-Silicon(FPGA), Silicon on engineering Chip validation platforms using Data Center Server OS/ARM Linux.

  • Test Plans development and validation include various components of the platform including OS Kernel, CPU, Memory, IO interfaces(C2C ,USB, PCIe, Ethernet).

  • Designing and implementing automated testing frameworks to enhance verification processes, and reliability in our testing pipelines using LLM / Gen AI tools for Stress and Stability testing.

  • Create workloads and identify appropriate tools to validate new chip features and functionalities.

  • Work closely with Multi-functional teams like hardware ASIC, FPGA teams, SW development teams on new requirements, products or features/improvements of existing products, test plans and test methods.

  • Troubleshoot bugs and provide resolution, you will play a key role in fixing bugs.

What we need to see:

  • Graduate/Post Graduate in Computer Science/Electronics/Telecommunication

  • At least 3+ years of Extensive Test development, execution/Validation experience on pre-silicon and Silicon in area of Embedded/SoC (Android/Linux/WOA) platforms

  • Strong hands-on experience in Windows on Arm (WOA) and GPU validation, including test planning, execution, debug, and issue closure on SoC/platform bring-up.

  • Solid understanding of SoC architecture, platform bring-up, and IP-level validation (e.g., USB, display, GPU, LSIO), with the ability to debug issues across HW, FW, and SW.

  • Practical knowledge of AI/LLM fundamentals and how to apply them to validation - for example, test strategy, log/trace analysis, triage, and test-tool development.

  • Proven ability to use GenAI and LLM tools to optimize test strategies, automate script/harness generation, and improve coverage, cycle time, and debug efficiency.

  • Proven ability to design and develop custom validation tools, test frameworks, and automation infrastructure.

  • Experience creating workloads and test methodologies to exercise chip features, including stress and stability testing.

  • Hands-on validation experience on key interfaces such as PCIe, USB3, CPU, and memory, or equivalent SoC/platform interfaces.

  • Strong knowledge of Linux kernel, bootloader, device-driver, and firmware testing, along with virtualization concepts and multicore/multiprocessing fundamentals.

Ways to stand out from the crowd:

  • LLM, GenAI Experience (tools like Cursor / Codex etc)

  • GPU validation experience

  • Experience in using an Analyzer/Oscilloscope

  • Show previous experience with IP-level test plan and test cases development with Embedded / Chipset / Data Center - Server Platforms.

  • Proven track record of delivering complex projects and automation solutions - from planning through execution - with tangible, production-ready outcomes.

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA’s GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Come be a part of this exciting world, at NVIDIA.

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, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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