Summary
Artem Chernodub is a Staff Machine Learning Scientist with 10 years of experience specializing in Generative AI, large language models, and NLP, currently building AI agents at Zendesk from Krakow. He combines deep academic roots—a PhD in AI and a history of published ACL work—with product-focused R&D experience at Grammarly, where he led a team that shipped personalized and “beyond-GEC” text rewrite features for millions of daily users. Artem has a strong track record of moving models from research to production, pioneering LLM fine-tuning and automated prompt optimization while designing A/B tests and metrics calibration. He also teaches deep learning at the master’s level and mentors theses, bridging industry practice with academia. Earlier roles span computer vision, behavioral biometrics, and search engine research, reflecting a rare comfort across modalities and end-to-end ML systems. Notably, his open-source argument-mining tagger from a DAAD-funded fellowship attracted community attention and fed into ACL-recognized work.
10 years of coding experience
10 years of employment as a software developer
Complete secondary education, Complete secondary education at Kyiv Natural Science Lyceum No. 145
Master of Science (M. Sc.), Applied Mathematics and Applied Physics, Master of Science (M. Sc.), Applied Mathematics and Applied Physics at Moscow Institute of Physics and Technology (State University) (MIPT)
Bachelor of Science (B. Sc.), Applied Mathematics and Applied Physics, Bachelor of Science (B. Sc.), Applied Mathematics and Applied Physics at Московский Физико-Технический Институт (Государственный Университет) (МФТИ)
Doctor of Philosophy (Ph.D.), Artificial Intelligence, thesis: Training the Dynamic Neural Networks for Long-Term Predictions, Doctor of Philosophy (Ph.D.), Artificial Intelligence, thesis: Training the Dynamic Neural Networks for Long-Term Predictions at Institute of Mathematical Machines and Systems Problems of NASU
English