Architecture Energy Modeling Engineering Intern - 2027

NVIDIA
Shanghai
Workplace: OnsiteFull timeFunction: Architecture & Urban PlanningEducation: mastersSkills: ["Verbal communication","Written communication","Interpersonal skills","Algorithmic thinking"]

Collaborate with architects, performance engineers, and software/ASIC teams to develop and deploy energy-efficient GPU models. Build methodologies and workflows to run workloads, train models using ML and/or statistical techniques, and improve model accuracy across design constraints. Correlate early predictions with silicon results, prototype architectural features, and integrate energy models into simulation, RTL, and emulation platforms while providing tools to debug energy inefficiencies.

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FursaFursa
NVIDIA
NVIDIA
2 hours ago

Architecture Energy Modeling Engineering Intern - 2027

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Last checked: 2 hours agoStatus: Live

Job Summary

Collaborate with architects, performance engineers, and software/ASIC teams to develop and deploy energy-efficient GPU models. Build methodologies and workflows to run workloads, train models using ML and/or statistical techniques, and improve model accuracy across design constraints. Correlate early predictions with silicon results, prototype architectural features, and integrate energy models into simulation, RTL, and emulation platforms while providing tools to debug energy inefficiencies.
Location: Shanghai
Workplace: Onsite
Employment Type: Full time
Job Function: Architecture & Urban Planning
Seniority: Intern level

Key Responsibilities

  • •Develop energy-efficient GPU models with architects and performance architects.
  • •Create methodologies and workflows to select and run workloads and train models using ML/statistical techniques.
  • •Improve energy model accuracy under constraints and correlate predictions across design stages to silicon.
  • •Develop tools to debug energy inefficiencies across silicon, RTL, and architectural simulators, and help fix issues.
  • •Integrate energy models into performance, verification, and emulation platforms; prototype architectural features and analyze system impact.

Key Requirements

  • •Pursuing an MS degree.
  • •Strong coding skills, preferably in Python and C++.
  • •Background in machine learning, AI, and/or statistical modeling.
  • •Interest in computer architecture and energy-efficient GPU designs.
  • •Familiarity with Verilog and ASIC design principles is a plus.
Experience:Machine learningAIStatistical modelingComputer architectureASIC design
Education:Master's
Skills:Verbal communicationWritten communicationInterpersonal skillsAlgorithmic thinking
Languages:English
Tech Stack:PythonC++MLAIStatistical modelingVerilogRTL simulationEmulationArchitectural simulatorsASIC designMachine learning

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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