Senior Accelerated Computing Architect

We are now looking for a Senior Accelerated Computing Architect!

NVIDIA is developing software and system architectures for accelerated high performance computing, scientific computing, machine learning, AI, datacenter, and automotive computing. This position offers you the opportunity to make a meaningful impact in a fast-moving, technology focused company.

Responsibilities

• Perform in-depth analysis and optimization to ensure the best possible performance on current and/or next-generation NVIDIA GPUs.
• Create and optimize core parallel algorithms, data structures, and reference codes to provide the best possible solutions for NVIDIA GPUs.
• Understand and analyze the interplay of hardware and software architectures on core algorithms, programming models, and applications.
• Actively collaborate with the hardware design, software engineering, product, and research teams to guide the direction of accelerated computing.
• Dive into accelerated computing applications to facilitate software-hardware co-design.
• Write up and present your work by writing white papers, conference publications, official blog posts, patent applications, etc. as appropriate.

Requirements

• An MS or Ph.D. in Computer Science, Computer Engineering or Electrical Engineering, or equivalent experience
• 6+ years of relevant work experience
• Strong mathematical fundamentals, including linear algebra and numerical methods.
• A passion for performance optimization.
• Hands-on experience with the massively parallel GPU programming model, e.g. CUDA or OpenCL. Familiarity with APIs for multi-node communication, like MPI or OpenSHMEM/NVSHMEM, is a plus.
• Strong knowledge of C and C++ with solid understanding of software design, programming techniques, and algorithms. Familiarity with threading APIs for multicore CPUs and Unix-style Inter-process Communication (IPC) APIs is a plus.
• Familiarity with Python is a plus.
• Good communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills.