Tomer Levinboim is a software engineer at Google Research with 12 years of experience building large multimodal language models and driving natural language generation research. He holds a PhD in ML/NLP from Notre Dame and has a strong academic pedigree including USC, TAU and Reichman, blending deep research with production engineering. Since joining Google in 2017 he’s applied statistical and neural approaches to low-resource language translation and large-scale model development. Early-career roles ranging from founding a prediction-market startup to backend development at Kenshoo give him practical systems and product instincts alongside research rigor. Based in Los Angeles, he combines algorithmic depth with hands-on software craftsmanship, often translating complex research into scalable code.
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