Rethinking ML System Design Interviews: Key Insights from My Journey
After engaging with around 15 companies during my ML/AI job search, it’s clear that outdated interview formats are holding us back. Here’s what I found:
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Common Pitfalls in Interviews:
- Vague Scenarios: Generic questions fail to stimulate thoughtful discussions. For instance, a scenario about preventing bank fraud should invite intricate questions instead of simple solutions.
- Inexperienced Interviewers: Interviewers often focus on specific areas instead of assessing the overall system, limiting the depth of candidate evaluation.
- Stale Problems: Many interview challenges do not keep pace with advancements, risking the assessment of irrelevant skill sets.
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Revolutionizing the Interview Loop:
- Replace antiquated ML system design questions with ones that reflect real-world scenarios.
- Focus on candidate growth potential, code quality, and adaptability in rapidly evolving contexts.
Let’s champion an interview system that positions us for success in AI and tech!
👉 Share your thoughts and experiences below! 📢
