Muhammed Sit is a Machine Learning Engineer with over a decade of hands-on experience and 6+ years specifically building production ML systems from research prototypes to deployed services. He currently contributes to Rovo Chat at Atlassian after leading multi-modal AI initiatives at PwC that delivered large-scale document intelligence and legal analysis tools saving millions annually and serving hundreds of thousands of users. His research background in transformer models, computer vision, and NLP includes publications at ICML and NeurIPS workshops, and he has a PhD-level informatics foundation from the University of Iowa. Technically fluent in PyTorch, LangChain, cloud-native architectures on AWS and Azure, and serverless inference patterns, he combines systems design with practical engineering—authoring graph-based agents, multilingual routing pipelines, and no-code deployment tooling for researchers. Known for squeezing latency and cost out of ML production (sub-5s p95 inference and significant projected savings), he also brings a rare blend of academic rigor and product-focused delivery across regulated domains like pharma. Based in Iowa City, he pairs deep research insight with pragmatic leadership of small engineering teams.
11 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy - PhD, Informatics, Doctor of Philosophy - PhD, Informatics at University of Iowa
Bachelor of Science (BSc), Computer Science, Bachelor of Science (BSc), Computer Science at İstanbul Şehir University
Contributions:13 commits, 11 pushes, 1 branch in 2 years 3 months
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Muhammed Sit - Machine Learning Engineer at Atlassian