Computer Vision Engineer

We are seeking a talented Computer Vision Engineer to design and develop mirror-aware, multi-camera perception systems for real-time human pose tracking. The role involves building robust 2D/3D pose estimation pipelines, handling occlusions and reflections, and optimizing performance for wearable and mobile devices. Key Responsibilities Design and implement multi-camera and mirror-aware computer vision architectures. Develop 2D and 3D human pose estimation systems. Implement camera calibration, stereo vision, and multi-view reconstruction pipelines. Perform mirror detection and reflection analysis using geometric consistency techniques. Develop algorithms for 3D joint triangulation and reprojection validation. Build real-time biomechanical analysis systems for posture, movement, and form correction. Implement temporal filtering and synchronization between camera streams. Optimize inference pipelines to achieve sub-100ms latency. Support ONNX and TensorFlow Lite (TFLite) model deployment. Create evaluation datasets, performance metrics, and automated testing frameworks. Required Skills Computer Vision Computer Vision Image Processing OpenCV Camera Calibration Stereo Vision Epipolar Geometry Multi-View Geometry 3D Reconstruction Feature Detection (SIFT, ORB, AKAZE) Homography & Geometric Transformations Pose & Video Analytics Human Pose Estimation 2D/3D Skeleton Tracking Video Processing Real-Time Streaming Multi-Camera Systems Temporal Filtering Programming Python NumPy SciPy OpenCV scikit-image C++ Git AI / Deep Learning MediaPipe YOLO HRNet ONNX TensorFlow Lite (TFLite) Edge AI On-Device Inference Preferred Qualifications Experience with multi-camera or stereo camera systems. Production deployment of Computer Vision applications. Experience with Edge AI and mobile deployment. Exposure to AR/VR, Robotics, Sports Analytics, or Fitness Technology. Familiarity with CVPR, ICCV, or ECCV research literature.