BlueSpace.ai

BlueSpace.ai

Mechatronics Engineer

Oakland, CA

Sponsorship not specified$130k-$200kDetected 889 days ago
PythonC++Distributed SystemsAlgorithmsLinuxExcelSolidWorksMechanical DesignElectrical EngineeringSensorsControlsResearchCommunication

About the role

  • Unlike conventional autonomy software, our patented 4D Predictive Perception removes reliance on data.
  • By leveraging next-gen 4D sensors, we can precisely predict the motion of all objects, increasing accuracy, lowering latency, and setting a new standard for safety and efficiency in autonomy.
  • Our team consists of seasoned professionals from across the autonomous vehicle (AV) ecosystem, including OEMs, world-class research institutions, and leading autonomous driving companies.

Requirements

  • Familiarity with interfacing sensors (cameras, lidars, radars, IMU, GPS), electronic control systems (DbW systems), and other components used in automated systems with unix-based systems.
  • Familiarity with programming with C++/python on unix based platform.
  • Ability to program necessary tooling software to troubleshoot interfacing issues with next-gen sensors and electronic control units.
  • Proficiency with 3D modeling CAD software (SolidWorks or Fusion360) B.S/ Master's degree in computer science, Mechanical Engineering, with a focus on mechanics, Electrical Engineering, or equivalent.
  • Experience with robotic middleware like ROS1.0, ROS2.0, rqt, rviz Experience deploying software for unix-based prototyping boards (e.g..
  • Working knowledge to troubleshoot and program for CAN and ethernet-based communications with sensors.
  • Proficient with using lab equipment for designing, building, and testing.
  • Ability to troubleshoot and improve existing equipment, design new equipment solutions, and ensure seamless integration of sensors and electronic control systems with software.
  • BlueSpace.aI is an Equal Opportunity Employer.

Compensation

  • $130k-$200k

This listing is sourced directly from BlueSpace.ai's careers page and normalized into a canonical job model.