Robotics/Autonomy Engineer - Computer Vision
Job in
Scottsdale, Maricopa County, Arizona, 85261, USA
Listed on 2026-07-25
Listing for:
Knightwerx
Full Time
position Listed on 2026-07-25
Job specializations:
-
Software Development
Robotics, AI Engineer (Applied/Software), Embedded Systems/ Firmware/ IoT
Job Description & How to Apply Below
- 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.
- 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).
- 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
- 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.
- 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
- 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.
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