Constantinos Dimitriou is a Senior Machine Learning Engineer with 11+ years building advanced audio and multimedia ML systems for products used across entertainment and media. He has driven production-grade research from source separation and vocal enhancement to transformer-based entity matching, combining deep learning, DSP, and robust training techniques to reduce artifacts and hallucinations. At Antares he led ML innovations for vocal prep and generative pitch models; prior roles at AudioShake and Gracenote produced state-of-the-art separation, lyrics alignment services, and multimodal embedding systems deployed in real products. He blends research rigor with practical engineering—designing datasets, evaluation protocols, and cross-team quality pipelines—to move models reliably into production. Based in San Francisco with a master’s in Sound & Music Computing and a BSc in Mathematics, he brings a rare mix of audio signal intuition and scalable ML engineering. An early background in music composition and web development subtly informs his product-oriented approach to audio research.
11 years of coding experience
15 years of employment as a software developer
Bachelor of Science (BSc) Mathematics, Bachelor of Science (BSc) Mathematics at University of Patras
Master's degree Sound and Music Computing, Master's degree Sound and Music Computing at Universitat Pompeu Fabra
Contributions:77 commits, 17 PRs, 47 pushes in 2 years 1 month
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Constantinos Dimitriou - Senior Machine Learning Engineer at Apple