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Avionics Powertrain Engineer (UAV Electrical Systems)

AirQ
Abu Dhabi, UAE
Full Time
Mid
Onsite
Today
Electric Powertrain DesignMATLAB/SimulinkPythonBLDC MotorsPMSMPower Electronics
Free

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Electric Powertrain DesignMATLAB/SimulinkPython
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Job Description

  • Seeking a highly skilled Avionics Powertrain Engineer to lead design, analysis, and optimization of electrical propulsion systems for UAV platforms.

Key Responsibilities

  • Perform electrical and system level calculations for UAV propulsion systems
  • Develop and validate powertrain architectures based on mission requirements
  • Conduct trade studies to optimize weight, efficiency, cost, and performance
  • Build and maintain simulation models (MATLAB/Simulink, Python) for motor performance, power electronics, battery energy usage, and thermal characteristics
  • Perform system level simulation to validate design decisions
  • Select and size electric motors (BLDC, PMSM), inverters/ESCs, batteries, and power distribution components
  • Evaluate supplier datasheets and validate performance against system requirements
  • Define interfaces between propulsion components and avionics systems
  • Support integration into UAV platforms
  • Collaborate with flight controls and software teams
  • Define test plans for powertrain validation
  • Analyze test data and refine models

Required Qualifications

  • Bachelor's or Master's degree in Electrical Engineering, Aerospace Engineering, or related field
  • Experience in electric powertrain design (UAV, aerospace, automotive, or robotics)
  • Strong understanding of electric motors, power electronics, and battery systems
  • Experience with simulation tools such as MATLAB/Simulink or Python

Preferred Qualifications

  • Experience with UAV propulsion systems
  • Familiarity with ESC design or motor control algorithms (FOC, PWM)
  • Knowledge of thermal management
  • Experience with hardware testing and lab instrumentation

Key Skills

  • Analytical thinking and problem solving
  • System level engineering mindset
  • Attention to detail
  • Cross functional collaboration

Deliverables / Success Metrics

  • Accurate simulations and validated models
  • Optimized component selection
  • Reliable and efficient powertrain performance
  • Reduced iteration cycles through quality analysis

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