Nvidia Senior Software Engineer - Python Numerical Computing Libraries 

United States, Texas 

399520744

What you will be doing:

• work closely with product management and internal or external partners, to understand use cases and requirements, and contribute to the technical roadmaps of libraries

• architect, prioritize, and develop accelerated and distributed implementations of numerical algorithms

• design future-proof Python APIs for accelerated numerical/scientific computing libraries

• analyze and improve the performance of developed APIs on various CPU and GPU architectures, especially as a part of customer-critical end-to-end workflows

• prototype integrations of developed APIs into targeted frameworks

• write effective, maintainable, and well-tested code for production use

• contribute to the development of runtime systems that underlay the foundation of multi-GPU computing at NVIDIA

What we need to see:

• BS, MS or PhD degree in Computer Science, Applied Math, Electrical Engineering or related field (or equivalent experience)

• 5+ years of relevant industry experience or equivalent academic experience after BS

• Excellent Python, C++ and CUDA programming skills

• Strong understanding of fundamental numerical methods, dense and sparse array computing

• Deep familiarity with Python numerical computing libraries (e.g. NumPy, SciPy), including accelerated implementations (e.g. CuPy, Jax.NumPy, NumS, cuNumeric)

• Experience developing and publishing Python libraries, following standard methodologies for pythonic API design

• Strong background with parallel programming and performance analysis

Ways to stand out from the crowd:

• Experience using/contributing to Python libraries for data science (e.g. Pandas), machine learning (e.g. scikit-learn) and deep learning (e.g. TensorFlow, PyTorch)

• Experience with low-level GPU performance optimization

• Experience building, debugging, profiling and optimizing distributed applications, on supercomputers or the cloud

• Background with tasking or asynchronous runtimes

• Background on compiler optimization techniques, and domain-specific language design