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About the role

Overview: In this role, you will advance GPU-accelerated database and ETL workloads by researching and implementing new techniques. You will collaborate with experts from industry and academia to analyze bottlenecks and optimize performance on modern architectures. You will influence hardware/software design directions across NVIDIA’s teams, contributing to cutting-edge systems. This position offers visibility and impact within a leader in GPU computing, with opportunities to publish findings and shape future technologies. You will work in a cross-functional, research-driven environment focused on high-performance data analytics. Compensation / Benefits equity benefits hybrid/remote options
Responsibilities: Research and develop GPU-accelerated techniques for high-performance databases and ETL applications Analyze complex data-intensive workloads to optimize performance on current GPU architectures Collaborate with research, hardware, system software, libraries, and tools teams to improve designs Influence next-generation hardware and software architectures and programming models Publish findings in developer blogs and conferences; engage with external technologists Support NVIDIA customers with performance insights and technical leadership
Key requirements: Master's degree (or PhD) in Computer Science, Computer Engineering, or related field 5+ years of relevant work or research experience Proficiency in C/C++ and solid software design fundamentals Hands-on experience with low-level parallel programming (CUDA, OpenACC, OpenMP, MPI, pthreads, TBB) Deep understanding of CPU/GPU architecture and memory subsystems Domain expertise in high-performance databases, ETL, and data analytics Strong communication and organizational skills clear communication organized problem solving prioritization CUDA OpenACC OpenMP

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JOB OVERVIEW

Experience level

Lead

Location

Brooklyn, NY

Occupation

Software Developers

Industry

Software Publishers

Posted

today

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