Muneeb R
Computer Vision Engineer: Video Analytics For Surveillance, Safety and Sports
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Experiência profissional
Computer vision and ML Engineer
HITAI • Período integral
Mar 2025 - Present • 1 yr 2 mos
At HITAI, I work as a Computer Vision and Machine Learning Engineer, where I design and implement intelligent systems for real-time image and video analysis. My role involves developing deep learning models, optimizing performance for deployment, and contributing to innovative AI solutions in the fields of object detection, action recognition, and visual tracking.
Head of AI Software Development
TADGT Group • Freelance
Sep 2025 - Dec 2025 • 3 mos
Leading the design and delivery of custom software and AI-driven solutions across multiple TADGT Group initiatives on a contract basis. Responsible for architecting and building scalable systems tailored to real business needs, including real-time computer vision applications, automation platforms, and custom internal tools. Working closely with commercial and operational teams to translate technical capabilities into practical, revenue-generating products. Key areas of work include: End-to-end development of AI-powered systems (computer vision, real-time analytics, dashboards) Designing MVPs and prototypes for rapid go-to-market validation Building scalable backend architectures and deployment pipelines Advising on technical strategy, performance, and future scalability Bridging the gap between engineering execution and business objectives Focused on delivering reliable, production-ready solutions while keeping systems simple, maintainable, and aligned with commercial goals.
Independent Computer vision & AI Projects
LinkedIn • Autônomo
Feb 2023 - Nov 2025 • 2 yrs 9 mos
Worked as an independent Computer Vision and Machine Learning Engineer, designing and delivering production-grade AI systems for real-world applications. Specialized in building end-to-end solutions covering data pipelines, model training, optimization, and deployment, with a strong emphasis on reliability, performance, and practical impact rather than research-only prototypes. Core work included object detection and tracking, action recognition, custom deep learning architectures, inference optimization, and deployment across edge and cloud environments. Engaged directly in problem decomposition, system design, model evaluation, and iterative improvement, translating complex business requirements into robust technical solutions.
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