Senior Accelerated Computing Architect

NVIDIA
Shanghai
Workplace: OnsiteFull timeFunction: Software EngineeringExperience: 6+ yearsEducation: mastersSkills: ["Performance optimization","Communication","Organization","Problem solving","Time management"]

Design and optimize accelerated computing software for NVIDIA GPUs across current and next-generation hardware. You will analyze performance, build and refine parallel algorithms, data structures, and reference code, and study hardware/software co-design across programming models and applications. Collaborate with hardware design, software engineering, product, and research teams, and communicate results through white papers, publications, blog posts, and patent applications.

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FursaFursa
NVIDIA
NVIDIA
1 month ago

Senior Accelerated Computing Architect

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Source: Company careers pageValidated by: Fursa AI
Last checked: 44 minutes agoStatus: Live

Job Summary

Design and optimize accelerated computing software for NVIDIA GPUs across current and next-generation hardware. You will analyze performance, build and refine parallel algorithms, data structures, and reference code, and study hardware/software co-design across programming models and applications. Collaborate with hardware design, software engineering, product, and research teams, and communicate results through white papers, publications, blog posts, and patent applications.
Location: Shanghai
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering
Seniority: Mid level

Key Responsibilities

  • •Analyze and optimize performance on current and next-generation NVIDIA GPUs.
  • •Create and optimize parallel algorithms, data structures, and reference code for NVIDIA GPUs.
  • •Study the interplay of hardware and software architectures across core algorithms, programming models, and applications.
  • •Collaborate with hardware design, software engineering, product, and research teams to guide accelerated computing direction.
  • •Write and present results through white papers, conference publications, blog posts, and patent applications.

Key Requirements

  • •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.
  • •Hands-on experience with massively parallel GPU programming models (e.g., CUDA or OpenCL).
  • •Strong knowledge of C and C++ with solid understanding of software design, algorithms, and programming techniques.
Experience:6+ years
Education:Master's
Skills:Performance optimizationCommunicationOrganizationProblem solvingTime management
Tech Stack:GPUCUDAOpenCLMPIOpenSHMEMNVSHMEMCC++PythonMulticore CPUsIPCUnix-style IPC

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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