ML interviewers favor practical problem solving and LLM-focused tasks over rote drills. In 2025 interview rooms, the emphasis is on how you think and how you frame a solution, not just memorized definitions, according to discussions [1].
What interviewers want to hear
- Clear ML basics explained with concrete examples [1]
- Ability to design ML solutions for ill-defined problems; crucial for senior roles [1]
- Walkthroughs of your project: data cleaning, model choices, metrics, and why; plus handling performance regression [1]
- Prepared to answer very hard questions and criticisms about your work [1]
- numpy-level coding and comfort with problem-style practice [1]
How to present your prior work
Drive the discussion, connect your work to the role, and be ready with a presentation you can show when asked [1].
Bottom line: practical problem solving, clear project storytelling, and reliability dominate LLM-era interviews [1].
References
[1]
Reddit
[D] ML interviewers, what do you wnat to hear during an interview?
Discussion on interviewer expectations for ML roles, with emphasis on LLM-related tasks and practical problem solving vs LeetCode in interviews.
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