The roadmap to becoming an ML engineer takes 36 weeks of mandatory study, with an additional 9 weeks for elective topics. The curriculum requires approximately 650 hours of work, averaging 18 hours per week. The path begins with foundational Python, mathematics, Git, and Linux, followed by classic machine learning and deep learning modules.
The author, an ML engineer at British Petroleum, mentored over 60 individuals in two years, 15 of whom secured positions. Data from 114 mentorship applications between September 2025 and September 2026 shows that 64% of candidates already work in IT, while 21% come from non-technical backgrounds. Applicants range from 17 to 56 years old and represent 19 countries.
Career goals are shifting toward remote work for foreign companies, with interest rising from 31% of candidates in early 2026 to 60% by March. While 52% of applicants aim for remote international roles, only 40% are fluent in English. Common barriers to entry include the complexity of higher mathematics and the need for practical project experience.
The study process emphasizes mock interviews after each major block to test knowledge. Recommended tools include Obsidian for note-taking and VS Code or Cursor for coding. The author notes that the job market experiences seasonal fluctuations, with fewer vacancies typically available toward the end of the year and in the month following the New Year.
