Michael Sharman is a Technical Program Manager with nine years of experience driving AI and data initiatives at leading labs, currently coordinating programs at OpenAI after roles at DeepMind and Microsoft. With a background in AI from Brunel University and hands-on experience as a data scientist, he bridges research and product delivery to operationalize machine learning at scale. He combines program leadership with practical engineering chops—his open-source contribution to Microsoft’s CNTK improved LabelMe-to-CNTK conversion for computer vision workflows. Based in London, he is skilled at aligning cross-functional teams, translating complex ML requirements into production-ready roadmaps, and optimizing developer usability in tooling and data pipelines.
9 years of coding experience
9 years of employment as a software developer
Bachelor's degree Computer Science (Artificial Intelligence), Bachelor's degree Computer Science (Artificial Intelligence) at Brunel University of London
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Role in this project:
ML Engineer
Contributions:8 commits, 3 PRs, 1 comment in 8 days
Contributions summary:Michael primarily contributed to a LabelMe conversion script within the CNTK repository, which is a deep-learning toolkit. The commits involved creating and refining a Python script to transform LabelMe annotation files (XML) into a format compatible with CNTK's image detection framework. These changes included initial script creation, output filename correction, and adjustments to the region of interest (ROI) output format, directly impacting the usability of CNTK for computer vision tasks.
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