Architect - GPU Performance

NVIDIA
Bengaluru
Workplace: HybridFull timeFunction: Hardware, Embedded & Systems EngineeringExperience: 3+ yearsEducation: mastersSkills: ["Debugging","Data analysis","Statistical analysis","Problem-solving","Collaboration"]

Work on system-level performance analysis for complex GPUs and System-on-Chips, identifying bottlenecks and improving turn-around time early in the product cycle. Build and use performance models, RTL test benches, emulators, and silicon-to-model workflows. Develop workloads and test suites across graphics, machine learning, automotive, and compute-vision use cases, partnering with architecture and design teams on trade-offs for area, power, and performance.

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FursaFursa
NVIDIA
NVIDIA
3 days ago

Architect - GPU Performance

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live
Reposted: similar role first listed 7 months ago

Job Summary

Work on system-level performance analysis for complex GPUs and System-on-Chips, identifying bottlenecks and improving turn-around time early in the product cycle. Build and use performance models, RTL test benches, emulators, and silicon-to-model workflows. Develop workloads and test suites across graphics, machine learning, automotive, and compute-vision use cases, partnering with architecture and design teams on trade-offs for area, power, and performance.
Location: Bengaluru
Workplace: Hybrid
Employment Type: Full time
Job Function: Hardware, Embedded & Systems Engineering
Seniority: Mid level

Key Responsibilities

  • •Perform system-level and bottleneck performance analysis for complex GPUs and System-on-Chips (SoCs).
  • •Develop and use performance models, RTL test benches, emulators, and silicon workflows to find performance bottlenecks.
  • •Understand product performance use cases and create workloads and test suites for graphics, machine learning, automotive, video, and compute vision applications.
  • •Partner with architecture and design teams to evaluate trade-offs across system performance, area, and power consumption.
  • •Build performance analysis infrastructure, including performance models, testbench components, analysis/visualization tools, and early-cycle performance methodology.

Key Requirements

  • •BE/BTech or MS/MTech in a relevant area; PhD is a plus or equivalent experience.
  • •3+ years of experience with performance analysis for complex SoCs and/or GPU architectures.
  • •Strong understanding of SoC architecture, graphics pipeline, memory subsystem architecture, and NoC/interconnect architecture.
  • •Hands-on programming in C/C++ and scripting in Perl/Python.
  • •Exposure to Verilog/SystemVerilog and SystemC/TLM is a strong plus, with debugging and analysis using RTL dumps.
Experience:3+ yearsGPU
Education:Master's
Skills:DebuggingData analysisStatistical analysisProblem-solvingCollaboration
Tech Stack:CC++PerlPythonVerilogSystemVerilogSystemCTLMRTLPerformance modelingEmulatorsTest benchesInterconnect fabricNoCGraphics pipeline

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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