As part of this role, you will develop an in-depth understanding of the overall CPU and GPU Architecture, Memory Management (HMM, UVM), programming language landscape, existing CUDA APIs, methods, and architectures for multi-node distributed computing, data locality, and migration, etc.
- Master’s degree in computer science, Electrical Engineer, Applied Mathematics, or related engineering field (Ph.D. preferred) or equivalent experience
- Experience and familiarity with scientific computing and AI (Artificial Intelligence) applications
- 6+ years’ experience developing/architecting software, libraries, and SDKs (software development kits)
- Additional 5+ years’ experience working as a Technical Product Manager in a Technology Company
- World-class communication skills with a proven ability to articulate a value proposition to technical and non-technical audiences.
Ways To Stand Out from the Crowd:
- Experience Developing/Architecting System Software
- Experience developing/architecting parallel, heterogeneous and/or large-scale software
- Deep understanding of system software & networking
- Background with CUDA or GPU computing