Product Validation Engineer

OmnivisionSanta Clara, CA
19d$90,500 - $140,000

About The Position

Product Validation Engineer is responsible for development of various CMOS imaging products. Responsibilities: Define test conditions, test methods and metrics to characterize CMOS image sensors Work with internal teams (Test Engineering, Design Verification) and bring up characterization test flow on ATE Validate ATE data with bench testing and measurements. Work closely with cross functional engineering groups to determine issue root cause (process, design or test) Determine how to validate sensor features, test and screen product features in mass production Develop test algorithms to target specific fail mechanisms Perform statistical data analysis on volume data, generate and present detailed performance reports for management to assess product readiness and risks. Find opportunities to optimize test methods, with coverage, potential overkill and test time being the biggest factors

Requirements

  • MS or BS in EE with 1-5 years equivalent work experience
  • In depth academic knowledge of semiconductor devices and circuits
  • Excellent communication and presentation skills
  • Dedicated and able to work with minimum supervision

Nice To Haves

  • Knowledge of Semiconductor Manufacturing Process and test equipment
  • Experience in programming with Scripting languages (PERL, Python)
  • Knowledge in CMOS image sensors is a plus
  • Experience with data analysis tools (JMP, Spotfire)

Responsibilities

  • Define test conditions, test methods and metrics to characterize CMOS image sensors
  • Work with internal teams (Test Engineering, Design Verification) and bring up characterization test flow on ATE
  • Validate ATE data with bench testing and measurements.
  • Work closely with cross functional engineering groups to determine issue root cause (process, design or test)
  • Determine how to validate sensor features, test and screen product features in mass production
  • Develop test algorithms to target specific fail mechanisms
  • Perform statistical data analysis on volume data, generate and present detailed performance reports for management to assess product readiness and risks.
  • Find opportunities to optimize test methods, with coverage, potential overkill and test time being the biggest factors
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