Sameeruddin Muhammad is a Melbourne-based Lead Generative AI Developer with eight years of Python-centric AI experience, blending research with production-grade cloud deployments on AWS. He specializes in computer vision for biodiversity monitoring, using object detection and image classification to analyze Australian fauna and is advancing this work through a PhD at La Trobe with an industry-focused, domain-specific CV lens. His strengths span training, evaluating, and maintaining ML models with TensorFlow, and delivering data-driven API services in distributed cloud environments, while recently leading Generative AI initiatives at BHP. He has collaborated with ecological organisations to build a data consortium for camera-trap data and has published work proposing faster, more accurate analysis—demonstrating a rare mix of science and practical impact. He is an avid learner and problem-solver who is actively exploring Retrieval Augmented Generation, small language models, and vision-language models to tackle complex partial appearances of fauna in camera traps, aiming to push AI for humanity. Based in Melbourne, he combines hands-on development across AI/ML, full-stack, and IoT-oriented projects with a track record of turning interdisciplinary ideas into scalable, real-world solutions.
8 years of coding experience
8 years of employment as a software developer
Bachelor’s Degree, Computer Science and Engineering, 76.2%, Bachelor’s Degree, Computer Science and Engineering, 76.2% at Vignan's Foundation for Science, Technology & Research
Advanced Diploma of Leadership and Management, Competent, Advanced Diploma of Leadership and Management, Competent at Angad Australian Institute of Technology
ACS Professional Year Program, Competent, ACS Professional Year Program, Competent at Performance Education
Doctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at La Trobe University
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