Why Are We HereIn the spring of 2024, as part of our product market research, I began conducting mock interviews and coaching people to prepare for their ML-related interview rounds. This experience was incredibly rewarding, as I had the opportunity to guide individuals through their challenges and received an outpouring of positive feedback. It has fueled my desire to continue on this path…
In many ML design scenarios, challenges around model supervision are common. These include issues such as noisy labels, limited labeled data, or labels that are only indirectly related to the target tasks. Demonstrating the ability to apply self-supervised and semi-supervised learning techniques to tackle these problems can significantly differentiate candidates by showcasing data-efficient and robust model designs. Among these techniques, contrastive learning stands…
Most ML System Design interviews start with a brief prompt, such as, "Design a recommendation system for XXX." This underscores the critical role of question clarifications. On one hand, interviewers use the clarification phase to assess candidates' communication skills and how effectively they articulate objectives. On the other hand, candidates rely on this step to gather the necessary context to steer the discussion…
User representation modeling is a critical component of personalized recommendation systems, making it both representative and scalable is a key challenge frequently discussed in ML system design interviews. At WWW '24, Meta published an insightful paper[1] on their online user modeling framework, which presents valuable design discussions and considerations. In this post, I’ll deep-dive this work using the Machine Learning System Design structure…
From my experience conducting hundreds of ML System Design interviews and nearly 100 mock interviews, poor time management is one of the most common reasons candidates struggle in the interviews. Many candidates fail to complete their design within the typical 45-minute to 1-hour timeframe, leaving interviewers without enough information to support hiring decisions. This issue affects a wide range of candidates, from fresh…