Radar Test Engineer - SPG

Santa Clara Valley (Cupertino), California, United States


Role Number:200295456
Apple SPG is looking for a Radar Test Engineer to join our Sensors team, which is developing new radar technologies for use in autonomous systems.

Key Qualifications

  • Have BS or MS degree in Electrical Engineering or Physics
  • RF academic and professional background
  • Hands-on testing of RF systems and subsystems including antennas, radomes, other RF passives, and RF solid-state devices
  • Have facility with Python, MATLAB, relevant MATLAB Toolboxes
  • Ability to manage, manipulate, process, and analyze large data sets
  • Experience with the development and oversight of RF test methods and fixtures


•Define, document, and execute test procedures and fixtures for experimentation, design verification, functional validation, and manufacturing •Design experiments for Radar performance characterization •Process, analyze, and review test data, compare with models and requirements •Develop and maintain automated test drivers and test software to interface and collect data from Radar sensors and Radar test equipment •Conduct post-test analysis of Radar data, draw conclusions, plan next steps •Effectively communicate Radar analyses, conclusions, and recommendations at pre- and post-test reviews to management •Plan, evaluate, procure, specify, and manage the development of test equipment and test facilities to characterize Radar sensors performance •Operate and maintain test facilities and equipment, and support test activities

Education & Experience

Additional Requirements

  • Preferred:
  • •MS plus 5 years experience
  • •Experience in robotics control and automation
  • •Working knowledge of common-bus and test equipment interface protocols
  • •Signal processing: waveform design, radar data cube processing, detector theory, estimation theory, point cloud filtering and compression
  • •Experience designing tests for mass production (>100,000 units per year)
  • •Interest in expanding abilities in data science, numerical analysis, engineering statistics & probability