Tal Galfsky is a Staff Machine Learning Engineer in New York with six years of experience bridging advanced physics research and applied data science. He transitioned from a Ph.D. in nanophotonics and senior photonics engineering roles into data science at Cherre, where he built production-ready ML solutions for large-scale real estate data before moving to Altos Labs. Tal combines deep experimental optics expertise with practical ML and engineering instincts, enabling him to tackle noisy, multi-source datasets and deploy robust models. His background negotiating high-stakes contracts and improving logistics processes hints at strong stakeholder management and operational rigor beyond pure engineering. Colleagues can expect a practitioner who blends academic rigor, hands-on instrumentation experience, and production ML delivery.
6 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.) - Expected in Oct 2016, Physics - nanophotonics, 3.8, Doctor of Philosophy (Ph.D.) - Expected in Oct 2016, Physics - nanophotonics, 3.8 at The Graduate Center, City University of New York
Bachelor of Science (B.Sc), Physics, 3.5, Bachelor of Science (B.Sc), Physics, 3.5 at Bar-Ilan University
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
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