Senior Deep Learning Performance Architect - LPU

NVIDIA
United States
Workplace: HybridFull time152,000 - 241,500 annuallyFunction: Data Science & Machine LearningExperience: 5+ yearsSkills: ["Collaboration","Problem-solving","Teamwork"]

Senior DL performance architect to design GPU/system architectures for AI inference, build power/performance models, and collaborate with software, research, and product teams to push AI efficiency and architecture decisions across NVIDIA’s AI stack.

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FursaFursa
NVIDIA
NVIDIA
6 months ago

Senior Deep Learning Performance Architect - LPU

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Source: Company careers pageValidated by: Fursa AI
Last checked: 22 hours agoStatus: Live

Job Summary

Senior DL performance architect to design GPU/system architectures for AI inference, build power/performance models, and collaborate with software, research, and product teams to push AI efficiency and architecture decisions across NVIDIA’s AI stack.
Location: United States
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Design novel GPU and system architectures to advance the forefront of AI Inference performance and efficiency
  • •Construct, investigate, and test popular deep learning algorithms and applications
  • •Understand and analyze the relationship between hardware and software architectures as it influences future algorithms and applications
  • •Build efficient power and performance models of AI inference stack, while capturing minimal but significant information to guide next-gen HW architecture
  • •Collaborate across the company to guide the direction of AI, working with software, research, and product teams

Pay and Benefits

Salary: 152,000 - 241,500 annually
Equity and Bonus:Equity

Key Requirements

  • •MS or PhD in CS, EE, Math or equivalent experience with 5+ years of relevant experience
  • •Strong mathematical foundation in machine learning and deep learning
  • •Expert programming skills in C, C++, and/or Python
  • •Familiarity with GPU computing (CUDA or similar) and HPC (MPI, OpenMP) stack
  • •Strong knowledge and coursework in computer architecture
Experience:5+ yearsAI hardwareDeep learningGPU computingHPCInference
Skills:CollaborationProblem-solvingTeamwork
Tech Stack:CC++PythonCUDAMPIOpenMPGPUKernelsASIC

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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