Senior Math Libraries Engineer - Sparsity in AI

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We are looking for software engineers to contribute to the design and development of libraries and tools to simplify and accelerate computing for unstructured sparsity in DL and HPC. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations, using data centers powered by GPUs and high-performance linear algebra libraries. Applications of these technologies include LLMs, computer aided engineering, quantum chemistry, autonomous vehicles, computer vision, and countless others. Did you know our team develops the GPU accelerated libraries and SDKs that help make these possible? In this role, you will work together with other developers on developing solutions that involve generalizations to sparse tensor computations, domain specific language (DSL) specifications of sparse storage formats, and on-demand code generation. Ideal candidates will not only have experience developing accelerated computing software, but also be motivated to advance the state-of-the-art in a variety of accelerated computing domains and DL frameworks like PyTorch. If this sounds exciting, we would love to meet you! What you will be doing: Design and develop a C++-based system to simplify and accelerate computing for unstructured sparsity in DL and HPC on NVIDIA GPUs Enable the system in languages and frameworks that are more commonly used in DL, such as Python and PyTorch Evaluate and improve the performance of the system on real-life applications Realize opportunities to improve library quality, performance and maintainability by writing effective and well-tested code for production use Work closely with product management and other internal and external partners to understand feature and performance requirements and contribute to technical roadmaps What we need to see: BS, MS or PhD degree in Computer Science, Applied Math, or related field (or equivalent experience) 6+ years of overall experience in developing, debugging and optimizing high-performance software using C++ and parallel programming; ideally for sparse linear algebra applications and using CUDA, MPI, OpenMP, or equivalent technologies Experience with domain-specific language design and compiler optimizations, in particular sparse compilers (MLIR or TACO) Excellent C++, Python, and CUDA programming skills Strong collaboration, communication, and documentation habits and ideally experience with working in a globally distributed organization Ways to stand out from the crowd: Strong understanding of sparse computations, in particular sparsity in AI and HPC Good understanding of LLMs, Deep Learning methods and frameworks Experience with low-level GPU performance optimization Understanding of numerical linear algebra methods like direct and iterative solvers Experience with adopting and advancing, software development practices such as CI/CD systems and project management tools such as JIRA. NVIDIA ’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing for science and engineering. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and build our teams with the smartest people in the world! Join us at the forefront of technological advancement. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Leve

我们正在寻找软件工程师，为简化并加速深度学习和高性能计算中非结构化稀疏性的计算，参与库和工具的设计与开发。在全球范围内，领先的商业和学术组织正在利用由GPU和高性能线性代数库驱动的数据中心，革新AI、数据分析以及科学与工程仿真。这些技术的应用包括LLM、计算机辅助工程、量子化学、自动驾驶汽车、计算机视觉以及无数其他领域。您知道我们的团队开发了助力实现这些可能的GPU加速库和SDK吗？在这个职位上，您将与其他开发者合作，开发涉及稀疏张量计算泛化、稀疏存储格式的领域特定语言（DSL）规范以及按需代码生成的解决方案。理想的候选人不仅应具备开发加速计算软件的经验，还应积极推动各种加速计算领域和PyTorch等深度学习框架的前沿发展。如果这听起来令人兴奋，我们很乐意与您见面！您将要做的工作：设计并开发一个基于C++的系统，以简化并加速NVIDIA GPU上深度学习和高性能计算中非结构化稀疏性的计算使该系统支持深度学习中更常用的语言和框架，例如Python和PyTorch在真实应用中评估并改进系统性能通过编写有效且经过充分测试的生产级代码，发现改进库质量、性能和可维护性的机会与产品管理以及其他内部和外部合作伙伴紧密合作，理解功能和性能需求，并为技术路线图做出贡献我们需要看到：计算机科学、应用数学或相关领域的学士、硕士或博士学位（或同等经验）6年以上使用C++和并行编程开发、调试和优化高性能软件的整体经验；理想情况下用于稀疏线性代数应用，并使用CUDA、MPI、OpenMP或同等技术具备领域特定语言设计和编译器优化经验，尤其是稀疏编译器（MLIR或TACO）优秀的C++、Python和CUDA编程能力良好的协作、沟通和文档习惯，最好有在全球化分布式组织中工作的经验脱颖而出的方式：对稀疏计算有深入理解，尤其是AI和HPC中的稀疏性对LLM、深度学习方法和框架有良好理解具备底层GPU性能优化经验理解数值线性代数方法，如直接和迭代求解器具备采用和推进软件开发实践的经验，如CI/CD系统，以及JIRA等项目管理工具。NVIDIA在1999年发明GPU，激发了PC游戏市场的增长，重新定义了现代计算机图形学，并彻底改变了科学与工程领域的并行计算。最近，GPU深度学习点燃了现代AI——下一个计算时代——GPU充当计算机、机器人和自动驾驶汽车的大脑，使它们能够感知和理解世界。如今，我们越来越被称为“AI计算公司”。我们希望通过世界上最聪明的人才来发展公司并建设团队！加入我们，站在技术进步的最前沿。NVIDIA被广泛认为是技术世界中最令人向往的雇主之一。我们拥有世界上最具前瞻性思维和才华的人才为我们工作。如果您富有创造力、自主性强并且热爱挑战，我们希望听到您的声音！您的基本工资将根据您的地点、经验以及类似职位员工的薪酬确定。基本工资范围为184,000美元至287,500美元（针对Leve

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