Masao Taketani is a Senior ML Engineer with eight years of hands-on experience building and deploying generative and recognition AI systems, now leading model development at Liquid AI. He has deep research-to-production expertise across diffusion models, GANs, VAEs, LLMs, VLMs and agentic AI, and a track record of adapting and extending major open-source stacks like HuggingFace Diffusers and Transformers. Masao combines a strong theoretical foundation—a master's in Information Science from the University of Tokyo focused on World Models and a BS in Statistics from the University of Minnesota—with practical skills in data engineering, training/finetuning, and production deployment including Dockerized demos. Previously he drove generative-AI R&D at HEROZ and built OCR and edge-deployed vision systems, reflecting a rare blend of academic curiosity and product-minded execution. Colleagues know him for turning paper ideas into reproducible code and insightful metric-driven analyses that improve model performance.
8 years of coding experience
7 years of employment as a software developer
Bachelor of Science - BS, Statistics, Bachelor of Science - BS, Statistics at University of Minnesota
Contributions:73 commits, 69 pushes, 1 branch in 6 months
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