Eugene Yan's guide to interviewing and hiring ML and AI engineers lays out a structured process from first contact to final decision. The focus is on identifying the skills that matter most for applied machine learning work, rather than generic programming puzzles or trivia.
The process starts with a phone screen, moves through a multi-stage interview loop, and ends with a debrief to align the hiring team on a candidate's strengths and gaps. Along the way, the article highlights specific signals to assess and offers tips for improving the experience for both interviewers and candidates.
Because this is a single source, there are no competing viewpoints to compare. The article is best read as a field guide from a practitioner, not a formal standard, and its advice can be adapted depending on team size and seniority.