Gabriel Levine is a Machine Learning Engineering Manager at Spotify with 11 years of experience leading data and ML engineering teams across product, R&D, and industrial applications. He has steered teams at large enterprises like Raytheon/Pratt & Whitney and United Technologies, and founded a creative tech collective that blends computational music, generative experience design, and ML tools for artists. Equally comfortable with production ML platforms and the research-to-deployment pipeline, he has a track record building systems for predictive maintenance, content platforms, and real-time data pipelines. A former professional musician and band founder, he brings a creative, cross-disciplinary perspective to engineering problems and product design. His background spans hands-on engineering, founding startups, and directing data organizations, combining technical depth in applied math and data science with an instinct for building teams that ship.
11 years of coding experience
14 years of employment as a software developer
Johns Hopkins University
The Graduate Center, City University of New York
Certificate, Advanced Calculus with Financial Engineering Applications, Certificate, Advanced Calculus with Financial Engineering Applications at Baruch College
Data Science, Data Science at General Assembly
The University of Texas at Austin
Master's degree, Applied Mathematics, Master's degree, Applied Mathematics at Hunter College
Bachelor's degree, Bachelor's degree at Connecticut College
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Gabriel Levine - Machine Learning Engineering Manager at Spotify