Computer Vision Engineer (Sports Video Analytics)

Що очікуємо

• Exceptional Python and deep understanding of PyTorch or TensorFlow.
• Strong foundation in classical computer vision geometry (projective geometry, epipolar geometry, camera matrices, OpenCV).
• Hands-on experience with modern tracking frameworks (e.g., ByteTrack, OC-SORT) or writing proprietary tracking logic.
• Experience optimizing models for inference (TensorRT, ONNX, Triton Inference Server).
• Engineering Mindset: Ability to profile vision algorithms, identify execution bottlenecks, and optimize for throughput/latency without losing precision.