Senior Software Engineer – Python Numerical Computing Libraries

🕒 April 9

🏄 California – Remote

🏄 California – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🔙 Backend Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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

🎯 Requirements

• BS, MS or PhD degree in Computer Science, Applied Math, Electrical Engineering or related field (or equivalent experience) • 6+ 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

🏖️ Benefits

• equity • benefits