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Micro LED Characterization Engineer

Sunnyvale, CARemote

AI Summary

Characterizes microLED devices optically, electrically, and thermally; builds and maintains automated test systems; analyzes performance and reliability data; drives root-cause analysis and cross-team optimization; develops test methods and mentors junior staff.

About this role

Responsibilities:

  • Perform optical, electrical, and thermal characterization of microLED devices throughout the development lifecycle.
  • Design, develop, and maintain automated measurement systems and test scripts to improve characterization efficiency and repeatability.
  • Analyze characterization data to extract key performance metrics, including optical output power, forward voltage, emission wavelength, external quantum efficiency (EQE), and device reliability/degradation characteristics.
  • Drive root cause analysis of device performance and reliability issues, providing data-driven recommendations to process, device, and design engineering teams.
  • Collaborate cross-functionally with process integration, epitaxy, device design, and product engineering teams to optimize device performance and manufacturing yield.
  • Develop new characterization methodologies, test procedures, and best practices to support next-generation microLED technologies.
  • Maintain, calibrate, and troubleshoot laboratory equipment to ensure measurement accuracy and reliability.
  • Document experimental procedures, results, and conclusions in clear technical reports and present findings to cross-functional teams.
  • Mentor junior engineers and technicians in characterization techniques, data analysis, and laboratory best practices.

Required Qualifications:

  • Bachelor's or Master's degree in Electrical Engineering, Physics, Materials Science, Optics, or a related technical field.
  • 10+ years of industry experience in semiconductor or optoelectronic device characterization.
  • Strong understanding of electrical, optical, and thermal characterization techniques for semiconductor devices.
  • Experience with automated test systems and measurement instrumentation.
  • Strong analytical skills with proficiency in JMP, Python, Excel, or similar data analysis tools.
  • Experience with statistical data analysis and Design of Experiments (DOE).
  • Excellent troubleshooting, problem-solving, and root cause analysis skills.
  • Strong written and verbal communication skills, with the ability to present technical findings to multidisciplinary teams.
  • Ability to work independently in a fast-paced startup environment while collaborating effectively across engineering disciplines.

Preferred Qualifications:

  • Ph.D. or M.S. in Electrical Engineering, Materials Science, Physics, Optics, or a related field.
  • Direct experience with microLED, LED, VCSEL, laser, or other III-V semiconductor device characterization.
  • Familiarity with metrology tools such as Scanning Electron Microscopy (SEM), optical microscopy, profilometry, and other optical characterization techniques.
  • Experience with reliability testing, failure analysis, and lifetime characterization.
  • Experience developing automated test software using Python, LabVIEW, or similar programming environments.
  • Knowledge of semiconductor fabrication processes and process integration.

Avicena is a privately held company developing microLED based ultra-low power high bandwidth interconnects for chip-to-chip communications.  This technology will revolutionize High-Performance (HPC) and Cloud computing, as well as other industries where low power interconnects are critical like camera sensors, autonomous vehicles, and aerospace. Avicena is headquartered in Sunnyvale, California with a development center in Edinburgh, Scotland. The company was founded in 2019 by leading technologists from the optical networking industry with a track record of delivering breakthrough products.  (www.avicena.tech) 

Skills

Automated Test SystemsDesign Of Experiments (DOE)Electrical CharacterizationExcelJMPOptical CharacterizationPhotoluminescencePythonSEMThermal Characterization

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