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Embedded engineer

  • On-site
    • Austin, Texas, United States
    • Boston, Massachusetts, United States
    • Kirkland, Washington, United States
    • New York, New York, United States
    • San Francisco, California, United States
    • San Jose, California, United States
    • Seattle, Washington, United States
    +6 more
  • Engineering

Job description

At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Embedded Engineer to join one of our clients' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.

About the Role: A skilled Embedded/IOT engineer is needed. You’ll play a key role in developing and deploying autonomous drone systems across a variety of platforms. This position focuses on system integration, navigation, and autonomy — not just simulation. You'll be part of a small, hands-on team doing meaningful, high-impact work in autonomy and aerospace. While not required, experience with PX4, QGC, VOXL 2, SLAM, and edge computing is a strong plus.

Key Responsibilities:

  • Develop and integrate PX4/ArduPilot-based flight control systems.

  • Work with QGroundControl and MAVLink for mission planning, telemetry, and data analysis.

  • Integrate navigation and guidance systems using GPS, IMUs, cameras, and other onboard sensors.

  • Collaborate with engineers working on autonomy, perception, and controls.

  • Support field testing and system validation in real-world environments.

Benefits:

  • 401k Matching

  • Dental, Vision, Health, Life Insurance

  • Paid Time Off

  • Holiday Pay

  • Relocation Assistance

Job requirements

  • 3–5 years of professional software engineering experience.

  • Proficient in C++ and Python.

  • Bachelor’s or Master’s in Electrical Engineering, Aerospace, Computer Science.

Bonus Experience:

  • Experience with PX4/Ardupilot

  • VOXL 2 (Qualcomm RB5 or similar) development and integration.

ROS2, Docker Experience:

  • SLAM or visual-inertial odometry (VIO).

  • Real-time edge computing and embedded systems experience.

  • Motion planning and autonomous navigation algorithms.

  • Computer vision for perception and tracking on UAV platforms.

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