Software Engineering Manager - CUDA Python

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. 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. We're looking to grow our company, and form teams with the most inquisitive people in the world. Join us at the forefront of technological advancement. 

We are looking for experienced software professionals to lead/extend our work on bringing delightful developer and user experience to the Python ecosystem. Our goal is to grow NVIDIA’s accelerated Python offerings to a mature product and make Python one of the first-class citizens for programming NVIDIA CUDA GPUs. You will be a crucial member of a team that is working to bring together the power of GPU acceleration and the expressibility and programmability of Python, by developing foundational software that supports many key products spanning the gamut of high performance computing, scientific computing, data analytics, deep learning, and professional graphics running on hardware ranging from gamer laptops to supercomputers to the cloud. 

What You'll Be Doing: 

As a member of our team, you will use your leadership skills, design abilities, coding expertise, creativity, and community engagement to develop and enhance the functionality and performance of NVIDIA GPUs such that the current and future generations of Python users can enjoy the programmability and take full advantage of the NVIDIA CUDA platform, including both NVIDIA hardware and software. Specifically, you will be working to: 

• Lead, mentor, and grow your engineering team and be responsible for the planning and execution of projects as well as the quality, and performance of projects in CUDA Python 

• Work closely with Product Management and Program Management teams to help collect requirements for your products as well as contribute to the development of roadmaps 

• Architect, prioritize, and develop new features in CUDA Python 

• Analyze, identify, and improve the UX and performance of CUDA software in Python 

• Bridge the language gap between existing CUDA C++ solutions and Python 

• Understand and address unique challenges in developing and deploying Python GPU solutions 

• Identify key open source players in the Python/PyData ecosystem, and engage with them to develop and drive necessary protocols and standards for the NVIDIA CUDA platform 

• Evangelize CUDA programming in Python to encourage and empower adoption of the NVIDIA CUDA platform 

What We Need To See: 

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

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

• 3+ years of experience recruiting, training and leading software engineering teams 

• Strong written communication, collaboration, and presentation skills with ability of operating across team boundaries 

• Experience with agile software development practices and a passion for driving adoption of high-performance software engineering practices 

• Strong Python programming and deployment skills with track record of driving formulation and/or adoption of Python community standards 

• Experience in designing, developing, tuning, navigating, and/or maintaining a large, complex, multi-language software stack (between C++/CUDA and Python) 

Ways To Stand Out From The Crowd: 

• Deep understanding in the CUDA programming model and language features 

• Familiarity with Python ecosystem, language idioms, and pioneering solutions 

• Experience contributing to or managing open-source software projects 

• Dexterity with compilers, static/dynamic analysis techniques, and/or dynamic code generation/transpilation/compilation 

• Experience in using or developing the LLVM/Clang compiler infrastructure as well as background in memory management of a multi-language project or development of domain specific libraries/languages for AI, Data Analytics or Scientific Computing