QA Test Developer at NVIDIA

Bengaluru, Karnataka, India

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Not SpecifiedCompensation

Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

Semiconductor, TechnologyIndustries

Requirements

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 (QNX/Android/Linux) platforms
Leverage GenAI and LLM tools to optimize testing strategies, automate script generation, and enhance validation efficiency
Ability to compile/cross compile tools/binaries for Embedded/ARM64 platforms
Proven ability to design and develop custom validation tools, test frameworks, and automation infrastructure
Strong programming skills in Python/C/C++, and Shell scripting (Bash/PowerShell)
Experience creating workloads and test methodologies to exercise and validate chip features / Stress and Stability testing
Confirmed Testing experience on key interfaces such as PCIe, USB3, CPU/Memory or equivalent experience
Knowledge of Linux Kernel, Boot loader, Device drivers testing, and Firmware testing
Understanding of Virtualization concepts, Multicore/Multiprocessing fundamentals
Ways to stand out
LLM, GenAI Experience (tools like Cursor etc)
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
A track record of solving problems with tangible solutions
Demonstrate delivery of complex projects/Automation solutions/Project planning in previous roles

Responsibilities

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

Skills

Python

C/C++

Shell scripting

Bash

PowerShell

Linux

ARM64

FPGA

Pre-Silicon validation

Silicon validation

PCIe

USB

Ethernet

GenAI

LLM

QNX

Android

OS Kernel

Automation frameworks

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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