A Bit More About Modern ML Education

Recently, I shared my thoughts on the preparation of AI specialists in the USA, China, and Russia. I mentioned that many of my acquaintances wrote their PhDs or master's degrees directly in the companies where they worked - this is the easiest way to get into research positions after graduation. Many people ask me if it is possible to become a Research Scientist in one of the large AI labs without a PhD. It is not common, but some people manage to get into research teams without a PhD: for example, one talented graduate from Yandex's School of Data Analysis managed to go from Machine Learning Engineer to Applied Scientist without graduate school. Meet Maxim Shaposhnikov. He graduated from the Ural Federal University with a degree in mathematics and mechanics, went to work in fintech during his master's program, and enrolled in the School of Data Analysis. Immediately after graduation, Max joined Amazon, where he worked on text-to-speech synthesis for Alexa and the audiobook service. It was there, through many formalities, reviews, and approvals, that he was able to get the opportunity to conduct research within the corporation. This is indeed a rarity in the West, and such determination deserves respect. I know several other successful researchers without a PhD (I met them at Meta), but these are also rather exceptional cases, and if you want to become a researcher, I would still advise pursuing a PhD - it is a more straightforward path, albeit a challenging one. By the way, Max is currently working at the startup Tessl, where they are developing tools for smart code generation. Here is the full story of his career path, check it out if you are also interested.