Manager, Solutions Architecture - Data Processing

NVIDIA is currently seeking a Solutions Architect Manager for Data Processing!

Would you enjoy researching new algorithms and memory management techniques to accelerate data processing on modern computer architectures? Do you like investigating hardware and system bottlenecks, and optimizing performance of data intensive applications? Are you excited about the opportunity to work on the top tier edge of technology with both visibility and impact to the success of a leader like NVIDIA?

In this role, you will lead a data processing SA team to research and develop techniques to GPU-accelerate high performance database, ETL and data analytics applications and new AI data processing technologies.

Responsibilities:

• Lead a data processing SA team to research and develop techniques to GPU-accelerate high performance database, ETL and data analytics applications and new AI data processing technologies.
• Work closely with industry and academia in China to perform in-depth analysis and optimization of complex data intensive workloads to ensure the best possible performance of current GPU/CPU architectures.
• Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.
• Influence partners to push the bounds of data processing with NVIDIA’s full product line.

Requirements:

• Masters or PhD in Computer Science, Computer Engineering, or related computationally focused science degree or equivalent experience.
• 8+ overall years of experience including 3 years management experience.
• Programming fluency in C/C++ with a deep understanding of algorithms and software design.
• Hands-on experience with low-level parallel programming, e.g. CUDA, OpenACC, OpenMP, MPI, pthreads, TBB, etc.
• In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.
• Domain expertise in high performance databases, ETL, data analytics and/or vector database.
• Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.

Nice to Have:

• Experience optimizing/implementing database operators or query planner, especially for parallel or distributed frameworks.
• Background with optimizing vector database index build and/or search.
• Experience profiling and optimizing CUDA kernels.
• Background with compression, storage systems, networking, and distributed computer architectures.