Nvidia Senior Software QA Test Development Engineer 

India, Maharashtra, Pune 

603372721

What you will be doing:

• QA & Prompt Design for Generative AI: Evaluate image/video outputs from generative AI models using thoughtful test prompts and clear quality metrics like realism, coherence, and safety.

• Automation & Tooling: Build and maintain Python-based tools, automation frameworks, and CI/CD test integrations to streamline QA workflows and improve test coverage.

• Graphics and Gaming Validation: Develop and implement detailed test plans for NVIDIA application software, which includes testing leading PC games. Emphasize NVIDIA features that improve visual quality, performance, compatibility, and overall user experience in authentic gaming environments.

What we need to see:​

• B.E./B. Tech degree in ComputerScience/IT/Electronicsengineering with strong academics or equivalent experience

• 5+ years of programming experience in Python/C#/C++ with experience in applying Object-Oriented Programming concepts

• Automation Expertise: Practical experience with test automation tools (e.g., Selenium), Git, and integration into CI/CD pipelines.

• Gaming & Hardware Knowledge: Deep understanding of PC gaming, GPU features, and testing on Windows systems; experienced with solving hardware/software interactions.

• Communication & Partnership: Strong critical thinking, clear documentation, and partnership in hybrid, multi-functional environments.

• QA Leadership: Experience mentoring QA teams or leading structured test planning efforts.

• Generative AI QA Experience: Hands-on testing or usage of image/video models (e.g., Sora, DALLE, Stable Diffusion), with Prompt engineering and evaluation of hallucination, relevance, and safety.

Ways to stand out from the crowd:

• Deep AI Evaluation Skills: Designed evaluation protocols for diffusion/video models using structured Prompt testing and perceptual metrics.

• Computer Vision Background: Strong understanding of image/video quality, human perception, and content alignment in AI outputs.

• Python & ML Libraries: Hands-on experience with AI/ML libraries like PyTorch, OpenCV, PIL, Transformers, and NumPy.

• GPU & Graphics Expertise: Familiarity with NVIDIA technologies (DLSS, G-SYNC, PhysX, or equivalent experience), display drivers, and PC visual quality benchmarks.

• Proactive Problem Solver: Known for creatively identifying root causes in sophisticated QA issues and working to improve processes.