May 2025 – Present · 10 mos · Greater Quebec City Metropolitan Area · Remote

• I'm happy to share that I'm joining MindsDB as an Advisor.
• MindsDB is focused on fascinating and, in my view, crucial aspect of applied AI: seamlessly integrating machine learning capabilities directly into the data layer.
• They empower developers to leverage existing databases as predictive engines, using the familiar language of SQL. This dramatically lowers the barrier to building AI-powered applications, abstracting away much of the traditional MLOps complexity.
• As you most likely know if you read this post, making advanced technology accessible and understandable has always been a core theme in my work. The approach Jorge and the team have taken – bringing AI to where the data lives and to the tools developers already master – resonates deeply with me.
• I see significant potential in the product and the team's vision to democratize AI adoption within the broader software engineering community.
• I will mainly contribute by:
• Helping in defining product features, making sure MindsDB continues to solve real-world developer problems with elegance and power.
• Hosting webinars designed to clearly demonstrate the simplicity and versatility of MindsDB for software engineers.
• We'll explore practical applications and, of course, I'll be diving into how it all works "behind the scenes" to provide that deeper understanding.
• I believe MindsDB is on a compelling trajectory, and I look forward to being part of their journey and engaging with the community.

May 2024 – Present · 1 yr 10 mos

• "This book cleared up a lot of conceptual confusion for me about how Machine Learning actually works—it is a gem of clarity. The worked examples and notebook applications gave me a solid starting point for exploration. Even if you are not planning a career in machine learning applications, this is a solid foundation for thinking about the capabilities of these unique new tools.” —Vint Cerf, Internet pioneer and Turing Award recipient
• "The book is a good start for anyone new to language modeling who aspires to improve on state of the art." —Tomáš Mikolov, the author of word2vec and FastText

Sep 2019 – Present · 6 yrs 6 mos

• “If you intend to use machine learning to solve business problems at scale, I'm delighted you got your hands on this book.”
• Cassie Kozyrkov, Chief Decision Scientist at Google
• “Foundational work about the reality of building machine learning models in production. Comes at the right time when companies start to see through the AI hype, realizing it takes a conscious engineering effort and best practices to make machine learning work. Another great book from Andriy!”
• Karolis Urbonas, Head of Machine Learning and Science at Amazon
• Released on Amazon, B&N, and Leanpub. Drafts are available on http://www.mlebook.com.

Jan 2019 – Present · 7 yrs 2 mos

• Peter Norvig, Research Director at Google, co-author of AIMA, the most popular AI textbook in the world: "Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing the topics — both theory and practice — that will be useful to practitioners, and for the reader who understands that this is the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field."
• Aurélien Géron, Senior AI Engineer, author of the bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: "The breadth of topics the book covers is amazing for just 100 pages (plus few bonus pages!). Burkov doesn't hesitate to go into the math equations: that's one thing that short books usually drop. I really liked how the author explains the core concepts in just a few words. The book can be very useful for newcomers in the field, as well as for old-timers who can gain from such a broad view of the field."

Feb 2023 – Mar 2025 · 2 yrs 1 mo · Greater Quebec City Metropolitan Area · Hybrid

• Leading the team of Machine Learning developers digging through the gigabytes of talent marketplace data.
• Tools and techniques used: machine learning (deep/shallow, LLMs, classification, generative AI, clustering, topic modeling), regular expressions, Python, MySQL, scikit-learn, PyTorch.

Nov 2015 – Jan 2023 · 7 yrs 2 mos · Quebec, Canada

• Leading a team working on "hacking" text and other unstructured or semi-structured data to extract useful information. Problems successfully solved by me and my team include:
• conversational user interfaces (chatbots);
• parsing of free-form résumé to detect and extract candidate name, employers, skills, certifications, employment history;
• parsing of job descriptions to detect and extract job title, salary, employer name, assign a standard occupation code;
• automated noisy and multi-language data normalization, cleanup, deduplication;
• novel data detection;
• language detection / text segmentation by language;
• sequence labeling (queries, addresses, salaries);
• machine translation;
• Web-data analysis.
• Tools and techniques used: machine learning (deep/shallow, classification, clustering, topic modeling, structured output prediction), regular expressions, Java, Python, MySQL, scikit-learn, Keras.

Apr 2013 – Nov 2015 · 2 yrs 7 mos · Capitale-Nationale, Quebec, Canada

• Turning terabytes of job announcements from online job boards into structured knowledge: extraction and classification of skills, standardization of job titles, classification of job announcements by an occupational classification, extraction/cleanup of structured data (company names, proper names, salaries, skills, etc), extraction and standardization of postal addresses, fuzzy duplicate identification (announcements, skills).
• Tools: linux shell scripting, MySQL, Sphinx, Python (scikit-learn, NLTK), Java.

Apr 2011 – Apr 2013 · 2 yrs · Quebec, Canada

• Computer scientist with the focus on applying machine learning and natural language processing in the context of big data; technology intelligence lead.
• Technologies: R, Python, Hadoop, HBase.

Jan 2011 – Apr 2013 · 2 yrs 3 mos · Quebec, Canada

• Working on research contracts for the Defence Research and Development Canada (DRDC).
• Research projects mostly turned around the problems of fusion of sensor data and intelligent software assistants.
• Technologies: Scilab.

Sep 2005 – Dec 2010 · 5 yrs 3 mos

• Research in multiagent systems resulted in multiple publications in top international conferences and journals (AAMAS, AAAI, Journal of Algorithms).