Solution Architect for High-Performance Databases

NVIDIA
Beijing, Shenzhen
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsSkills: ["Communication","Organization","Problem solving","Prioritization"]

Research and develop techniques to GPU-accelerate high-performance database, ETL, and data analytics applications. Work with technical experts to analyze and optimize complex, data-intensive workloads for today’s GPU architectures. Collaborate across research, hardware, system software, and libraries teams to influence next-generation hardware architectures, software, and programming models, and to help partners expand NVIDIA’s data processing capabilities.

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FursaFursa
NVIDIA
NVIDIA
2 days ago

Solution Architect for High-Performance Databases

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Last checked: 16 hours agoStatus: Live

Job Summary

Research and develop techniques to GPU-accelerate high-performance database, ETL, and data analytics applications. Work with technical experts to analyze and optimize complex, data-intensive workloads for today’s GPU architectures. Collaborate across research, hardware, system software, and libraries teams to influence next-generation hardware architectures, software, and programming models, and to help partners expand NVIDIA’s data processing capabilities.
Location: Beijing, Shenzhen
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Research and develop techniques to GPU-accelerate high-performance database, ETL, and data analytics applications.
  • •Perform in-depth analysis and optimization of complex data-intensive workloads for best performance on current GPU architectures.
  • •Collaborate with research, hardware, system software, and tools teams to influence next-generation hardware architectures, software, and programming models.
  • •Influence partners in industry and academia to expand data processing using NVIDIA’s full product line.
  • •Work directly with other technical experts to optimize performance and address system and hardware bottlenecks.

Key Requirements

  • •Masters or PhD in Computer Science, Computer Engineering, or a related computationally focused science degree (or equivalent experience).
  • •5+ years of 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 preferred; OpenACC, OpenMP, MPI, pthreads, TBB, etc.).
  • •In-depth expertise with CPU/GPU architecture fundamentals, especially the memory subsystem.
Experience:5+ years
Education:
Skills:CommunicationOrganizationProblem solvingPrioritization
Tech Stack:C/C++C++CCUDAOpenACCOpenMPMPIPthreadsTBBRAPIDS cuDFNvcompCUDA kernelsSparkVector databaseCPU/GPU architectureMemory subsystem

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
Glassdoor
Glassdoor: 4.3
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