Requirements:

• PhD or Master’s degree in Computer Science, Applied Math, or related science or engineering field of study (or equivalent experience)
• 5+ years of experience in designing, developing, testing, maintenance, and performance optimization of production software using CUDA and C++
• Good knowledge of GPU (preferred) or CPU hardware architecture
• Strong fundamentals in finite precision arithmetics and numerical methods for linear algebra
• Great teamwork, communication, and documentation habits

Nice to haves:

• Experience with CUTLASS, or low level programming like assembly for performance optimization is a huge plus
• A scripting language, preferably Python
• Experience with working in a globally-distributed team

What you will be doing:

• Scoping, designing, and implementing high quality and performance numerical dense linear algebra software on GPUs
• Providing technical leadership and feedback to library engineers working with you on projects and sometimes mentor interns
• Working closely with product management and other internal and external customers to understand feature and performance requirements and help define the technical roadmaps of libraries
• Finding opportunities to improve library performance and reduce code maintenance overhead through re-architecting

Perks and benefits:

• Competitive salaries
• Generous benefits package
• Opportunity to work with some of the smartest people in the world
• Rapidly growing exclusive engineering teams