Engineer - Optical Communication Systems (Test, Modeling & Sensing)

Huawei

$106K — $156K *
Telecommunications & Hardware
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. in Photonics, Optical Communications, Electrical Engineering, Physics, or a closely related field.
  • 3+ years of post-Ph.D. or industry experience in optical fiber communication or sensing systems.
  • Strong hands-on laboratory skills and familiarity with optical test equipment.
  • Proficient in modeling optical wave propagation and programming in Python, MATLAB, or C++.
  • Solid understanding of coherent optical communication, advanced modulation formats, and DSP for optics.
  • Experience with machine learning/AI techniques for optical performance monitoring is an asset.
  • Knowledge of control systems for dynamic optical networks is a plus.

Responsibilities

  • Bridge theoretical modeling with experimental validation to enhance optical fiber systems.
  • Oversee the entire system lifecycle, from simulation and optimization to rigorous testing.
  • Design and automate advanced optical laboratory testbeds for system performance validation.
  • Characterize optical components for system performance evaluation.
  • Develop numerical models considering linear/nonlinear impairments and optimize systems for efficiency.
  • Implement algorithms for real-time optical performance monitoring and fault detection.
  • Analyze experimental data to root cause anomalies and optimize system parameters.

Benefits

  • Opportunities for career advancement in a cutting-edge field.
  • Access to advanced tools and technologies for experimental work.
  • Collaboration with leading experts in optical fiber communication.
  • Engagement in innovative projects with a real-world impact.
  • Support for continued education and professional development.
Full Job Description
  • You will bridge the gap between theoretical modeling and hands-on experimental validation to advance the next generation of optical fiber communication and sensing systems.
  • Your work will span the entire system lifecycle - from high-fidelity simulation and optimization to rigorous experimental testing, real-time performance monitoring, and advanced fault detection:
  • Design, build, and automate advanced optical laboratory testbeds to validate system-level performance. Conduct characterization of optical components (transceivers, amplifiers, fibers, and modulators).
  • Develop and maintain accurate numerical models of optical transmission systems, accounting for linear/nonlinear impairments (e.g., CD, PMD, SPM, XPM). System optimization for maximum capacity, reach, and efficiency.
  • Design and implement algorithms for real-time optical performance monitoring (OPM) and predictive fault detection to enhance network reliability and automated telemetry.
  • Explore and develop fiber-optic sensing capabilities (e.g., DAS, DTS, DSS) or utilize existing communication infrastructure for co-designed communication and sensing applications.
  • Analyze large datasets from experimental setups and field trials to root-cause anomalies, optimize system parameters, and close the loop between simulation and reality.

The total target annual compensation for this position ranges from $106,000 to $156,000 depending on education, experience, and demonstrated expertise.

  • Ph.D. in Photonics, Optical Communications, Electrical Engineering, Physics, or a closely related field.
  • 3+ years of post-Ph.D. or industry experience in optical fiber communication or sensing systems.
  • Strong hands-on laboratory skills. Deep familiarity with optical test equipment (e.g., Optical Spectrum Analyzers (OSAs), Real-Time Oscilloscopes, Bit Error Rate Testers (BERTs), Optical Time-Domain Reflectometers (OTDRs)).
  • Proficient in modeling optical wave propagation (e.g., solving the Nonlinear Schrödinger Equation). Strong programming skills in Python, MATLAB, or C++ for simulation, data analysis, and lab automation.
  • Solid understanding of coherent optical communication, advanced modulation formats (QAM, QPSK), digital signal processing (DSP) for optics, and fiber non-linearities.
  • Experience with machine learning/AI techniques applied to optical performance monitoring or fault prediction is an asset.
  • Knowledge of control systems for dynamic optical networks is an asset.

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