Senior Accelerated Computing Architect

NVIDIA
Santa Clara
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 6+ yearsEducation: mastersSkills: ["CUDA","OpenCL","C++","C","Python","MPI","OpenSHMEM","NVSHMEM","Multithreading","Unix IPC"]

Lead and optimize performance for NVIDIA GPUs in high-performance computing and AI workloads. Design and implement parallel algorithms, study hardware-software co-design, and collaborate with hardware, software, product, and research teams to push GPU architectures to their limits. Publish findings and contribute to papers/blogs while mentoring teams across hardware and software domains.

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FursaFursa
NVIDIA
NVIDIA
2 months ago

Senior Accelerated Computing Architect

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Source: Company careers pageValidated by: Fursa AI
Last checked: 4 hours agoStatus: Live

Job Summary

Lead and optimize performance for NVIDIA GPUs in high-performance computing and AI workloads. Design and implement parallel algorithms, study hardware-software co-design, and collaborate with hardware, software, product, and research teams to push GPU architectures to their limits. Publish findings and contribute to papers/blogs while mentoring teams across hardware and software domains.
Location: Santa Clara
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Sr. Manager level

Key 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.

Pay and Benefits

Equity and Bonus:Equity
Perks:Equity

Key Requirements

  • •MS or PhD 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
  • •Hands-on experience with the massively parallel GPU programming model (CUDA or OpenCL)
  • •Strong knowledge of C and C++ with solid software design, programming techniques, and algorithms
Experience:6+ yearsHigh performance computingGPU computingAccelerated computingCUDAOpenCL
Education:Master's
Skills:CUDAOpenCLC++CPythonMPIOpenSHMEMNVSHMEMMultithreadingUnix IPC
Languages:English
Tech Stack:CUDAOpenCLCC++PythonMPIOpenSHMEMNVSHMEMUnix IPCGPUs

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
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Glassdoor: 4.3
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