Summary
Vineeth Mohan is a senior machine learning engineer and researcher with a decade of experience building and scaling probabilistic deep learning and recommender systems for large enterprises. He has led AI initiatives at Visa—driving fraud detection, transaction prediction, and a novel conversational model for transaction data—and currently works on ML at Adobe in the Bay Area. His work bridges rigorous research (PhD-level publications and patents) with product impact, emphasizing Bayesian deep learning, uncertainty estimation, and generative models for heterogeneous, large-scale data. He has a proven track record of improving production rankings and recommendation accuracy through contextual embeddings and Siamese transformer architectures, and published applied ML research at venues like CVPR and RecSys. Colleagues value his ability to translate complex probabilistic models into documented, deployable systems that meet latency and business constraints.
10 years of coding experience
11 years of employment as a software developer
Phd Computer Engineering, Phd Computer Engineering at Wayne State University