Karl Hayek is a Machine Learning Engineer based in Paris with nine years of experience building and deploying audio and NLP-driven ML systems for industries from music streaming to healthcare. He has designed production-grade pipelines and CI/CD for large-scale audio processing—supporting research and daily automated workloads across 100K+ tracks at Deezer—and now focuses on improving speech-to-text solutions for healthcare at Nabla. His background spans music information retrieval, lyrics alignment, vocal isolation, beat-tracking, recommendation systems, and computer vision, reflecting a strong applied-research to production delivery arc. Trained at the American University of Beirut with software studies at UC Berkeley, he combines academic NLP experience (medical QA chatbots) with hands-on engineering in Docker/Kubernetes and PyTorch. Notably, Karl has contributed to projects that enabled licensing deals and built dashboards indexing hundreds of millions of audio fingerprints, showing an ability to translate research prototypes into business-impacting products.
9 years of coding experience
7 years of employment as a software developer
Summer Session Software Engineering, Summer Session Software Engineering at University of California, Berkeley
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at American University of Beirut
Cookiecutter template for Flask API projects at the Innovation Lab
Contributions:2 PRs, 28 pushes, 1 branch in 3 months
apipythonflask-apiflaskcookiecutter-template
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