Autonomous Navigation Engineer, Advanced


    Website ZebraTechnology Zebra Technologies


    The ideal candidate should have substantial experience designing navigation systems for autonomous platforms operating in indoor environments. This includes expertise in at least one of the following areas: sensor calibration, object detection, simultaneous localization and mapping, path planning, and low-level controller design. They should take ownership of their work, be self-motivated & practical in their problem-solving and thrive in a fast-paced, highly collaborative applied research environment.


    • Develop and maintain scalable codebase used to calibrate sensors and actuators used on a robot system including: Camera Intrinsic, Extrinsic, White-balance calibration of both standard and fisheye cameras, Time-of-Flight cameras, Lidar, IMU, Odometry
    • Support integrating SLAM solutions with larger robotics navigation systems
    • Design and develop user-friendly and automated process for mapping large environment with minimum human intervention
    • Collaborate with algorithm developers and researchers to come up with scalable real-time autonomous navigation solutions and support them in software implementation
    • Troubleshoot sensor driver problems by contacting manufacturers and novel optimization and filtering methods
    • Working with pointclouds and image data for classification, tracking, and geometric estimation
    • Applying machine learning techniques for the purposes of geometrical analysis and tracking
    • Designing and testing algorithms for long-term deployment (many months without failures)
    • Integrating solution with larger robotics navigation system
    • Understanding and accounting for the effects that navigation design decisions have on the larger robotic system, including mechanical and electrical designs
    • Take initiative and lead the systematic evaluation for proposed algorithms


    • Masters in Computer Engineering/Computer Science (preferably with specialization in computer vision and machine learning); alternatively a comparable industry career, with significant experience in delivering products using state-of-the-art computer vision and/or machine learning systems
    • 8+ years work experience
    • Broad understanding of computer vision; key areas of interest include object detection, tracking and recognition, multiple view geometry, OCR detection, camera calibrations, 3D data processing, SfM/SLAM, activity recognition
    • Significant latitude used in determining objectives of assignment
    • Optimization experience on embedded GPU and DSP platforms: Nvidia, ARM
    • Parallelized & vectorized computation
    • Solid GPU programming experience using CUDA or Open CL
    • Excellent C, C++11 and above programming skills
    • Experience in signal processing algorithms and implementation

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