Full-Time

Software Quality Assurance Tools Development Engineer

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

No salary listed

Pune, Maharashtra, India

In Person

Onsite at Pune office; relocation support not specified.

Category
QA & Testing (1)
Required Skills
LLM
Python
Git
SQL
Machine Learning
Quality Assurance (QA)
.NET
REST APIs
Android Development
Linux/Unix

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Requirements
  • Engineering degree in Computer Science, IT, Electrical and Computer Engineering, or a related field, with strong academic performance
  • 5+ years of total experience with excellent programming skills in Python and C#, including the ability to write logical scripts and code from scratch
  • Demonstrated ability to design, build, and deploy AI/ML and agentic AI solutions to accelerate automation development and testing workflows
  • Strong familiarity with AI-native development tools such as Codex, Claude Code, Cursor, and large language model APIs to improve engineering velocity
  • Clear understanding of large language model failure modes, including hallucination and context degradation and prevention methods
  • Working experience with .NET Core, SQL for persistent data storage and queries, and version control tools such as GitHub and Perforce
  • Strong understanding of PC hardware and Operating Systems architecture (Windows, Linux or Android)
  • Hands-on experience with Linux environments, including advanced scripting and command-line operations
  • Ability to manage conflicting or changing priorities while maintaining a positive attitude in an ambitious and dynamic environment
  • Ability to work with geographically dispersed teams and attend reviews or meetings to maintain alignment
Responsibilities
  • Utilize various certification kits to test software and hardware features of our products, ensuring certification-level quality across all stages of the development cycle, from emulation to production. This includes a wide range of functional areas such as graphics, display, audio, multimedia, USB, hypervisors, and virtual machines
  • Develop a thorough understanding of all functional and process-related areas within the hardware and functional certification ecosystem
  • Work actively with existing UI and automation tools by integrating internal and external APIs, formulate and deploy multi-agent systems to optimize existing workflows and to build new automated solutions
  • Communicate accurate, timely, and effective status updates to management and key internal and external partners
  • Drive operational excellence by defining and improving processes, using innovative problem-solving methods to increase organizational efficiency and support strategic goals
  • Represent the team in internal meetings such as release planning, bug scrubs, and project status reviews, as well as external discussions with certification authorities and partners
  • Engage with software development teams when reporting certification bugs, providing key debugging information and data points to help drive timely closure
  • Collaborate with the broader QA team to identify opportunities for leverage and to build tools that can help large scale use cases
  • Become a champion of quality for every NVIDIA product you work on, and help promote that same mindset across the team and cross-functional organizations

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • Rubin delivers 5x faster inference and 3.5x faster training than Blackwell starting H2 2026.
  • Major hyperscalers Microsoft, AWS, Google Cloud, and CoreWe confirmed Vera Rubin implementation ahead of Q3 2026.
  • Rubin Ultra targets 15 ExaFLOPS FP4 inference with 1.5 PB/s NVLink bandwidth per rack in 2027.

What critics are saying

  • HBM4 scarcity from SK Hynix and Micron forces Rubin production cut to 1.5M units in 2026.
  • Kyber NVL144 rack delayed to 2028 due to TSMC 78-layer PCB yield failure, breaking annual cadence.
  • Rubin Ultra cuts HBM4E stacks to 12-Hi, delivering only 2.66x instead of 4x performance gain.

What makes NVIDIA unique

  • Vera Rubin is a six-chip extreme codesigned AI supercomputer platform, not just a GPU.
  • NVIDIA shifted to annual architecture cadence with Rubin, Ultra, and Feynman releases through 2028.
  • Vera CPU with 88 ARM cores enables per-GPU efficiency and 1/10 Blackwell operational costs.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-2%

2 year growth

-3%
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