Silicon Performance, Power and Binning Tools Engineer

NVIDIA
Shanghai
Workplace: OnsiteFull timeFunction: Energy & Utilities OperationsExperience: 4+ yearsEducation: bachelorsSkills: ["Debugging","Data quality","Problem-solving","Collaboration","Staying current"]

Build and connect AI-driven toolchain pipelines that transform raw silicon simulation data (power, noise, binning yields) into firmware tuning, product specs, and manufacturing limits. Use LLMs and agents to automate analysis, validation, and reporting currently done manually. Develop observability and validation to prevent data issues from blocking releases, and collaborate across silicon architecture, firmware, and manufacturing teams to translate new hardware requirements into production workflows.

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FursaFursa
NVIDIA
NVIDIA
23 hours ago

Silicon Performance, Power and Binning Tools Engineer

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 23 hours agoStatus: Live

Job Summary

Build and connect AI-driven toolchain pipelines that transform raw silicon simulation data (power, noise, binning yields) into firmware tuning, product specs, and manufacturing limits. Use LLMs and agents to automate analysis, validation, and reporting currently done manually. Develop observability and validation to prevent data issues from blocking releases, and collaborate across silicon architecture, firmware, and manufacturing teams to translate new hardware requirements into production workflows.
Location: Shanghai
Workplace: Onsite
Employment Type: Full time
Job Function: Energy & Utilities Operations
Seniority: Mid level

Key Responsibilities

  • •Build infrastructure that converts raw simulation data into firmware tuning, product specs, and manufacturing limits, owning the pipelines between tools.
  • •Use LLMs and agents to automate analysis, validation, and reporting across the toolchain.
  • •Create observability and validation systems to catch data errors and inconsistencies before release blockers.
  • •Collaborate with product convergence, silicon architecture, firmware, and manufacturing teams to translate hardware requirements into production workflows.
  • •Translate new hardware capabilities into workflows that downstream firmware, manufacturing, and specification systems can consume.

Key Requirements

  • •BS/MS in CS, CE, EE, or Systems Engineering, or equivalent experience.
  • •4+ years of experience in a related hardware/software position.
  • •Strong understanding of digital design, circuit analysis, algorithms, computer architecture, silicon speed and power, BIOS, drivers, and software applications.
  • •Experience with Perl/Python, databases, and web applications.
  • •Hands-on experience applying LLMs to engineering problems (agents, MCP, RAG, or evaluation pipelines) with production impact and strong data-quality instincts.
Experience:4+ yearsSiliconHardwareSoftwareAILLM-based engineering
Education:Bachelor's in CS, CE, EE, or Systems Engineering
Skills:DebuggingData qualityProblem-solvingCollaborationStaying current
Tech Stack:LLMsAgentsMCPRAGPerlPythonDatabasesWeb applicationsObject-oriented programmingSchema validationIntegration testsObservabilityDashboardsVisualizations

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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