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Senior Accelerated Computing Architect

NVIDIA · Santa Clara, CA · 3 wk ago
EngineeringFull-time

About the role

This position offers the opportunity to make a meaningful impact in a fast-moving, technology-focused company. The Senior Accelerated Computing Architect will perform in-depth analysis and optimization to ensure the best possible performance on current and/or next-generation NVIDIA GPUs.

Responsibilities

  • Creating and optimizing core parallel algorithms, data structures, and reference codes to provide the best possible solutions for NVIDIA GPUs.

  • Understanding and analyzing the interplay of hardware and software architectures on core algorithms, programming models, and applications.

  • Actively collaborating with the hardware design, software engineering, product, and research teams to guide the direction of accelerated computing.

  • Diving into accelerated computing applications to facilitate software-hardware co-design.

  • Writing up and presenting 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

  • Experience benchmarking, profiling characterizing workloads on GPU and CPU clusters

Qualifications

  • A strong background in computer science, computer engineering, or electrical engineering

  • Experience with GPU programming and optimization

  • Excellent analytical and problem-solving skills

  • Ability to work effectively in a team environment

Skills

  • Proficiency in C/C++, CUDA, and OpenCL

  • Experience with parallel programming and optimization techniques

  • Knowledge of GPU architecture and memory systems

  • Experience with multi-node communication frameworks

  • Strong communication and collaboration skills

Benefits

  • NVIDIA is widely considered to be one of the technology world's most desirable employers

  • Equity and benefits are provided

Pay

The base salary range is $184,000 - $287,500 for Level 4, and $224,000 - $356,500 for Level 5.

Schedule

The schedule is flexible and can accommodate remote work options.

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