NVIDIA

Solutions Architect, Generative AI

NVIDIA

full-time

Posted on:

Location Type: Office

Location: Shenzhen • China

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About the role

  • Assisting field business development in guiding the customer build/extend their GPU infrastructures for AI.
  • Help customers build their large-scale projects, especially Large Language Model (LLM) projects.
  • Engage with customers to perform in-depth analysis and optimization to ensure the best performance on GPU architecture systems.
  • This includes support in optimization of both training and inference pipelines.
  • Partner with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers.
  • Enable development and growth of product features through customer feedback and proof-of-concept evaluations.
  • Build industry expertise and become a contributor in integrating NVIDIA technology into Enterprise Computing architectures.

Requirements

  • MS or PhD in Electrical Engineering, Computer Science/Engineering, Mathematics, Physics, or a related field (or equivalent experience).
  • 3+ years of work-related experience in AI for large language (or multi-modal) models, including model architecture or training strategy design, training optimization, inference acceleration, etc.
  • Proficient in using AI tools or agents to do your work.
  • Clear mind and thoughts in a logical and hierarchical manner.
  • Strong written and oral communications skills in English.
Benefits
  • NVIDIA is committed to encouraging a diverse work environment and proud to be an equal opportunity employer.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
GPU infrastructureLarge Language Model (LLM)training optimizationinference accelerationmodel architecture designAI toolsperformance analysisoptimization pipelinesproof-of-concept evaluationsEnterprise Computing architectures
Soft Skills
logical thinkinghierarchical thinkingwritten communicationoral communication
Certifications
MS in Electrical EngineeringPhD in Computer SciencePhD in MathematicsPhD in Physics