Production Application Engineer, Enterprise

NVIDIA NVIDIA · Semiconductors · Taipei, Taiwan +1

NVIDIA is seeking a Principal Production Application Engineer to manage GPU server production with contract manufacturers and ODMs, focusing on NPI builds, debugging, yield improvement, and ensuring production KPIs are met from evaluation to shipment.

What you'd actually do

  1. Own NPI builds from early engineering through ramp, ensuring smooth handoff to high‑volume production at contract manufacturers.
  2. Lead debug test configuration and flows, driving efficient FA and fast issue triage for manufacturing defects, yield issues, and bonepile recovery.
  3. Act as the primary technical leader for ODMs and contract manufacturers on L6, L10 and L11, covering production readiness, line setup, test, and yield.
  4. Work closely with internal HW/FW/SW and validation teams to track and close critical bugs quickly, ensuring designs are manufacturable (DFM/DFT).
  5. Be on‑site at factories as needed, coordinating with manufacturing teams to resolve issues in real time and help partners meet key production KPIs.

Skills

Required

  • Bachelor’s degree in EE, CS, Industrial/Manufacturing Engineering, or related field.
  • 5+ years in hardware system, production, manufacturing, or datacenter product engineering.
  • Strong experience working with ODMs/contract manufacturers on NPI and mass production.
  • Solid understanding of assembly, test, and quality processes, and how they affect yield.
  • Excellent problem‑solving and root cause analysis skills, with clear technical communication in English (spoken and written).

Nice to have

  • Hands-on experience in datacenter product engineering, failure analysis, debugging, or GPU server design.
  • Proven track record in managing production schedules at factories and monitoring yield rates.
  • Willingness and ability to travel internationally.
  • Excellent communication and teamwork skills to collaborate effectively across cross-functional teams.
  • Knowledge of Failure Mode and Effects Analysis (FMEA) // Root Cause Analysis (RCA) // Design of Experiments (DOE)

What the JD emphasized

  • primary interface
  • ownership
  • production KPIs
  • continuous process improvements
  • NPI builds
  • high-volume production
  • debug test configuration
  • manufacturing defects
  • yield issues
  • production readiness
  • line setup
  • test
  • yield
  • DFM/DFT
  • resolve issues in real time
  • production schedules
  • yield rates