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9 Mothers9 MothersAustin, TX

Computer Vision Engineer, Senior

Designs and optimizes embedded computer vision pipelines for real-time detection, tracking, and 3D localization of fast-moving drone threats in autonomous counter-UAS systems. Requires expertise in C++/Python, OpenCV, deep learning frameworks, sensor fusion, and edge deployment on NVIDIA Jetson.

150k – 250k
On-siteML Engineering

About the role

Responsibilities

  • Architect and implement the entire embedded CV pipeline using high-performance Python and C++.
  • Design and deploy robust multi-object tracking and sensor fusion algorithms for high-fidelity state estimation of fast-moving targets.
  • Utilize real-time models (e.g., YOLO) and CNNs optimized for speed.
  • Optimize code for low-latency performance on resource-constrained NVIDIA Jetson environments using TensorRT and TFLite.
  • Apply principles of calibration, rectification, and 3D geometry to translate 2D footage into accurate 3D coordinates for fire control.
  • Collaborate with robotics teams to ensure reliable perception data for autonomous decision-making.

Requirements

  • Strong background in C++ (for performance) or Python.
  • Deep expertise in VIO, VO, and SLAM frameworks for real-time state estimation.
  • Proficiency in OpenCV and image-processing modules in PyTorch or TensorFlow.
  • Experience with DNN inference libraries (e.g., TensorRT, TFLite) for edge deployment.
  • Hands-on experience building embedded CV systems for real-time applications involving small, fast objects.
  • Deep understanding of camera calibration and 3D geometry.

Preferred Qualifications

  • Prior defense startup experience.
  • Security clearance or ability to obtain one.

Skills

C++PythonOpencvPyTorchTensorFlowTensorRTTfliteYoloSlamVioVoNvidia Jetson

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