Sameeruddin Muhammad is a Senior Data Engineer specialising in Geospatial AI with nine years of software engineering experience and seven years focused on Python-driven AI and computer vision. He builds and deploys distributed, cloud-native ML systems on AWS—training and maintaining TensorFlow models for object detection and image classification applied to Australian biodiversity and camera-trap imagery. As a PhD candidate, he combines academic rigor with industry collaboration, having established a national data consortium of species camera-trap data and published a paper proposing a faster, high-accuracy analysis approach. His work spans the full ML lifecycle—from experimenting with CNNs and transformers to integrating RAG, small language models and vision-language models to surface complex partial-appearance identifications. Past roles show strong product-minded delivery: migrating services to serverless Lambdas to cut costs tenfold and shipping SaaS IoT solutions for real-world fauna detection. Based in Melbourne, he seeks projects that translate domain-specific research into operational tools that help ecological experts and drive measurable impact.
9 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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Sameeruddin Muhammad - Senior Data Engineer (Geospatial AI)