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A Machine Learning Engineer with a strong foundation in computer vision is sought by a provider of cutting-edge Tech Applications. Your core role will be to improve the quality and reliability of the deployed detection and classification models.
This is a hands-on role focused on model refinement, error analysis, and data-driven performance improvements rather than building from scratch. The successful incumbent will require 2+ years of Python & Machine Learning experience including computer vision Deep Learning models. You also need to be familiar with model serving and inference pipelines . Analyse and improve the performance of existing object detection and image classification models deployed in production.
Systematically investigate missed detections and false alarms across diverse CCTV environments, identify failure patterns, and propose targeted fixes. Design and implement data augmentation strategies tailored to real-world CCTV challenges such as varying lighting, camera angles, resolution, weather conditions, and occlusion. Run controlled experiments to evaluate the impact of training strategies, hyperparameter changes, data balancing, and architectural tweaks on model performance. Contribute to the development and refinement of false positive filtering pipelines, including ensemble and verification-based approaches.
Assist with data labelling workflows, quality checks, and dataset preparation for training and evaluation. Maintain clear records of experiments, results, and model performance metrics to support reproducibility and team knowledge sharing. Work on ML Backend development for the production system and support infrastructure. Experience with computer vision Deep Learning models.
Familiarity with model serving and inference pipelines . Familiarity with annotation tools and labelling workflows .
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