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Nvidia Deep Learning Test Development Engineer Architect United States, California 457591910
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What you’ll be doing:
Work closely with DL engineering teams to develop a keen understanding of DL QA goals, test strategies, and technical needs.
Collaborate with diverse inter-groups, including DL Researchers, Product, and engineering teams to identify gaps, and improve processing.
Lead bug lifecycle and co-work with QA test developers to analyze customer bugs and user scenarios to improve test coverages.
What we need to see:
MS/PhD (PhD preferred) in CS, EE, Math or closely related fields or equivalent experience.
10+ years of software development experience in DL/ML, DL Framework (Especially JAX and PyTorch), Neural Networks, DL Service deployment, user scenario analysis and SDKs.
Able to design test strategies for diverse DL products to optimize test plans and identify the most essential and risky use cases.
Excellent C/C++, Python programming skills; Strong written and oral communications skills in English.
Ways to stand out from the crowd:
Be familiar with deep neural network training, inference, optimization in typical Frameworks.
Experience software development with popular AI models (e.g., LLM models)
Background with GPU computing and parallel programming such as CUDA/OpenCL.
You will also be eligible for equity and .
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