Deep Learning Performance Architect

NVIDIA
Shanghai, Beijing
Full timeFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: bachelorsSkills: ["Collaboration","Analytical thinking","Performance optimization","Problem-solving","Technical communication"]

Analyze state-of-the-art deep learning models (including LLMs) and prototype performance opportunities that influence NVIDIA’s current and next-gen inference software and architecture. Build analytical models for network algorithms to drive processor and system architecture designs focused on performance and efficiency. Define hardware/software configurations and metrics to evaluate performance, power, and accuracy across uni- and multi-processor setups, collaborating across architecture, software, and product teams to shape next-gen DL HW/SW direction.

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FursaFursa
NVIDIA
NVIDIA
1 day ago

Deep Learning Performance Architect

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Source: Company careers pageValidated by: Fursa AI
Last checked: 47 minutes agoStatus: Live
Reposted: similar role first listed 6 months ago

Job Summary

Analyze state-of-the-art deep learning models (including LLMs) and prototype performance opportunities that influence NVIDIA’s current and next-gen inference software and architecture. Build analytical models for network algorithms to drive processor and system architecture designs focused on performance and efficiency. Define hardware/software configurations and metrics to evaluate performance, power, and accuracy across uni- and multi-processor setups, collaborating across architecture, software, and product teams to shape next-gen DL HW/SW direction.
Location: Shanghai, Beijing
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Analyze state-of-the-art deep learning networks (including LLMs) and identify/prototype performance opportunities to influence SW and architecture teams for inference products.
  • •Develop analytical models for deep learning networks and algorithms to help innovate processor and system architecture designs for performance and efficiency.
  • •Specify hardware/software configurations and performance, power, and accuracy metrics for uni-processor and multi-processor setups.
  • •Collaborate across the company to guide next-gen deep learning HW/SW direction with architecture, software, and product teams.

Key Requirements

  • •BS, MS, or PhD in a relevant discipline (CS, EE, Math, etc.) or equivalent experience.
  • •5+ years of work experience.
  • •Experience with popular AI models, e.g., LLM and AIGC models.
  • •Familiarity with deep learning software frameworks such as Torch, JAX, TensorFlow, or TensorRT.
  • •Knowledge and experience in hardware architectures for deep learning applications.
Experience:5+ yearsDeep learningLLMAIGC
Education:Bachelor's in Computer Science, Electrical Engineering, Mathematics
Skills:CollaborationAnalytical thinkingPerformance optimizationProblem-solvingTechnical communication
Tech Stack:Deep LearningLLMAIGCTorchJAXTensorFlowTensorRT

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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