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Specialized CV skills, mid-seniority, and metro location create medium candidate density.
Strong domain bias: mission-critical, multi-camera, and edge CV experience limits cross-industry transferability.
Mandatory 5+ years CV/DL production experience plus specific frameworks and edge/real-time requirements increases filtering.
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Develop and optimize computer vision models for detection, segmentation, tracking, OCR, action recognition, and video analytics in airport apron operations.
Build and manage end-to-end video processing pipelines including ingestion, annotation, augmentation, training, evaluation, and inference.
Monitor and maintain model performance, accuracy, latency, resource usage, and adapt to environmental changes across cloud, data-centre, and edge platforms.
Bachelor’s or Master’s degree in Computer Science, AI, Electrical Engineering, Mathematics, or related discipline.
Minimum 5 years of production experience in computer vision or deep learning.
Proficiency in Python and frameworks like TensorFlow, PyTorch, or Keras; strong experience with OpenCV and video analytics techniques.
Experience with data preparation, model evaluation, deployment, monitoring, and MLOps; familiarity with real-time, multi-camera, edge, NVIDIA, or mission-critical systems preferred.
Experienced in handling operational challenges such as false positives, missed detections, model drift, and varying environmental conditions in production CV systems.
Capable of end-to-end ownership from experimentation through production deployment and monitoring in complex, real-time vision systems.
Effective communicator who can convey model confidence, limitations, and trade-offs and collaborate closely with cross-functional teams including domain experts and MLOps.