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Robotics/Autonomy Engineer - Computer Vision

Knightwerx
Scottsdale, AZ Full Time
POSTED ON 12/1/2025 CLOSED ON 1/2/2026

What are the responsibilities and job description for the Robotics/Autonomy Engineer - Computer Vision position at Knightwerx?

Job description

  • Knightwerx is seeking a highly skilled Robotics/Autonomy Engineer – Computer Vision to lead development and integration of advanced perception, vision-based navigation, and autonomy software for a small, unmanned electric aircraft. We operate in a fast-paced development environment that balances innovation and ingenuity with practicality and reliability. You’ll collaborate with flight-software, aeromechanical, and avionics teams to deliver robust autonomy for GPS-denied, contested, and complex environments from prototype through production. The role emphasizes cutting-edge computer vision, sensor fusion, and real-time autonomy algorithms to enable resilient operations in austere conditions.

Work Experience

  • Bachelor’s or higher degree in Computer Engineering, Electrical Engineering, Computer Science, Robotics, or a related discipline.
  • 5 years of relevant industry experience in computer vision, robotics, or embedded systems.
  • Proven experience developing image signal processing (ISP) and computer vision (CV) software.
  • Hands-on experience with MIPI Camera Serial Interface (CSI) and writing drivers for image sensors.
  • Experience integrating and operating camera systems in UAVs or other autonomous platforms.
  • Knowledge of video codecs (H.264/H.265) and network protocols for video transmission (RTSP, MPEG-TS).

Attributes

  • Effective collaborator in cross-functional team environments.
  • Open to feedback and committed to continuous improvement.
  • Innovative, hands-on, and practical in problem solving.
  • Multi-disciplinary mindset with strong engineering analysis skills.
  • Goal-driven, resilient, and accountable throughout the design process

Primary Duties

  • Design, develop, and optimize computer vision and ISP software for real-time robotic and UAV applications.
  • Implement and maintain camera drivers, video pipelines, and hardware-accelerated vision algorithms.
  • Integrate vision systems with navigation, control, and autonomy stacks.
  • Ensure software is scalable, maintainable, and efficient across embedded and distributed platforms.
  • Collaborate with hardware, systems, and autonomy engineers to deliver end-to-end solutions.
  • Participate in documentation of design, implementation, and test procedures.
  • Troubleshoot and debug system-level issues in camera and vision pipelines.
  • Stay current with emerging CV/ML methods, hardware accelerators, and best practices.

Tasks

  • Develop and optimize computer vision algorithms for perception, navigation, and target detection in GPS-denied and contested environments
  • Integrate vision systems with autonomy software, including sensor fusion, SLAM, and obstacle avoidance
  • Select, configure, and test vision sensors and compute payloads to support autonomous behaviors
  • Implement and validate real-time autonomy features using vision-based inputs and multi-sensor data
  • Ensure perception and autonomy software is scalable, maintainable, and efficient for prototype through production
  • Participate in rigorous field testing, data collection, and refinement of vision/autonomy performance
  • Document software design, algorithms, and test procedures for technical teams and stakeholders

Skills

  • Strong understanding of image formation, filtering, feature extraction, segmentation, optical flow, object detection, tracking, and recognition.
  • Experience with camera calibration (intrinsic/extrinsic) and time synchronization of multi-sensor data.
  • Proficiency with OpenCV, GStreamer, and V4L2.
  • Practical experience with hardware acceleration (CUDA, SIMD, Vulkan, etc.).
  • Familiarity with Nvidia Jetson platforms, FPGAs, and VPUs (Intel Movidius, Coral TPU).
  • Experience with deep learning–based CV methods (CNNs, transformers, object detection/segmentation frameworks such as YOLO, Faster R-CNN, Mask R-CNN, DETR, SAM, etc.).
  • Knowledge of classical CV methods (SIFT, SURF, ORB, HOG, Harris/FAST/ORB keypoints).
  • Understanding of image/video stabilization, SLAM, and 3D reconstruction fundamentals.
  • Experience with containerization (Docker) and container orchestration.
  • Proficiency with version control systems (Git) and build tools (CMake).
  • Strong programming skills in C , Python, and/or Rust.

Requirements

  • Must have US citizenship
  • On-site, collaborative work environment

Salary : $140,000 - $210,000

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