Senior Software Test Development Engineer - Deep Learning

Shanghai, Shanghai, China

• Category: Software Engineering

Description

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The position is in NVIDIA AI Software Quality Assurance team that defines, develops and performs tests to validate robustness and measure the performance of NVIDIA‘s AI software and GPU Infrastructure for autonomous driving, healthcare, speech recognition, natural language processing, and a wide variety of other AI scenarios. This team collaborates with multiple AI product teams to develop new products; derive and improve complex test plans; and improve our workflow processes for a diverse range of GPU computing platforms. You should grow with being in the critical path supporting developers working for billion-dollar business lines as well as intimately understanding the values of responsiveness, thoroughness and teamwork. You should constantly foster and implement efficiency improvements across your domain. Join the team which is building software which will be used by the entire world!

What you’ll be doing:

• Work closely with global cross-functional teams to understand the test requirements and take ownership of product quality.

• Plan/design/execute/report/automate test plan/test case/test reports.

• Manage bug lifecycle and co-work with inter-groups to drive for solutions.

• Automate test cases and assist in the architecture, crafting and implementing of test frameworks.

• In-house repro and verify customer issues/fixes.

What we need to see:

• BS or higher degree in CS/EE/CE or equivalent.

• 5+ years of software quality assurance or test automation background with knowledge of test infrastructure and strong analysis skills.

• Scripting language (Python, Bash) knowledge and UNIX/Linux experience.

• Good Python software development or test development experience.

• Good user/development experience of virtualization like VM & Docker container & k8s

• Excellent English written and oral communication skills.

• LLM user/developing/training/inference experience is must like GPT, Llama

• Inference framework like TensorRT / Triton or Dynamo direct use/develop experience is must

• Spark ETL and SQL developing experience. Machine Learning usage on bigdata (logistic regression, Kmean, knn, etc.)

• Proven success in leveraging AI (development) tools to significantly improve efficiency, streamline workflows, enhance process automation, create test cases and increase code coverage.

• Experienced on AI tools for coding (like Cursor, Gemini, NotebookLM)

Ways to stand out from the crowd:

• Experience with LLM inference frameworks (TRT-LLM, vLLM, SGLang, etc.) and familiar with running various AI workloads

• Familiarity with NVIDIA GPU hardware products (Tesla, Tegra, DGX, etc.)

• Understanding public cloud usage (AWS, GCP, Azure, etc.)

• Working knowledge of NVIDIA GPU Computing (CUDA) and CUDA libraries for Deep Learning like cuDNN

• Experience in VectorCAST, Bullseye, Gcov, or Coverity tools.

Company

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NVIDIA

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.