HWQA Engineer

expertise (SME) in the areas of So C 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/So C (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 So C/platform bring-up. Solid understanding of So C 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 Gen AI 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 So C/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, Gen AI 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. NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.