NVIDIA networking IC product engineering team is looking for talented IC failure analysis engineer to join failure analysis team and various activities of IC failures investigations in order to enable smooth products' bring up, optimizing yield and quality, handle customer returns, and be critical part of product qualification that requires root cause every failure encountered. The selected candidate will utilize ATE testers and system boards in combination with optical debug and fault isolation techniques such as: Laser stimulations (OBIRCH, LADA, etc.), Laser probing and emission microscopy, to identify defects, chip design marginalities, process issues and many more.
What you will be doing:
IC debug and fault isolation using ATE tester, system boards or other test equipment, in combination with optical techniques.
Modify test programs to fit FA requirement.
Interpret ATPG diagnosis reports
Prepare technical reports summarizing the findings and guide Physical FA engineers in their work and PFA plan.
Development of novel and existing debug techniques.
Working directly with the job requestors (Q&R, Foundry, physical design) and supporting teams (Test, DFT, SW, physical design).
What we need to see:
BSc/MSc/PhD degree in Electrical/Computer Engineering or Physics.
2+ years of experience in Failure analysis, Si debug or ATE test development.
Good understanding of VLSI circuit design, and/or device physics, and/or process engineering.
Programming experience and at least basic Python and Unix skills.
Ability to work independently, and as part of a team.
Strong sense of ownership, commitment, and responsibility
Effective oral and written communication skills.
Strong analytical problem solving
Ways to stand out from the crowd:
Familiarity with ATE Test Programs, and ability to adopt Test Patterns per debug needs
Statistical/data analysis experience (Matlab, JMP, etc.)
Hands-on experience with different EFA techniques such as: laser stimulations, laser probing, photon emission, thermal emission, TDR
Background with electronic test equipment: scopes, spectrum analyzers, etc.
Passionate in hands-on and lab-oriented environment.
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NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
