Summary
Vladislavs Dovgalecs is a Machine Learning Engineer with 13 years of experience applying probabilistic programming and predictive modeling to high-dimensional, often unlabeled data. He combines a strong academic background (PhD in Computer Science) with practical skill in building prototypes and production-ready solutions using Python, MATLAB, C/C++, and Java across UNIX environments. His work spans information retrieval, time series processing, NLU (intent recognition, NER, chatbots), and crowdsourcing for data labeling, with a particular interest in quantifying uncertainty in small-data settings. Comfortable selecting and customizing the right theoretical tools for fit-for-purpose, large-scale solutions, he has co-authored 12 publications and brings an applied-research mindset to product-focused engineering. Based in Bellevue, Washington, he is especially passionate about probabilistic approaches and their real-world ML applications.
13 years of coding experience
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Ventspils Augstskola
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at Université Bordeaux I
Ukrainian, Russian, Latvian, French, English