I was asked to discuss some LLM projects I had worked on, exploring the technical aspects and including one or two theoretical questions.
Machine Learning Intern Interview Questions
8,202 machine learning intern interview questions shared by candidates
How would I approach one case
A large part of the interview focused on my PhD thesis. After I explained my research at the beginning, the interviewers asked in-depth questions to assess how well I understood my own work. Later, they asked machine-learning–related questions relevant to the role, including hypothetical scenarios about how I would approach and analyze a given type of data etc.
Some fundamental machine learning questions and then a deep dive into RAG system components.
CNN mechanism, filters, pooling layers, Transformer mechanism, positional encoding
1. Explain the E2E architecture of a multi-agent system that you have built? 2. Explain how BERT works? 3. How do you evaluate RAG system?
How does K-means algorithm work
Q: Describe yourself? Q: What project are you the most proud of?
Describe a time when you disagreed with a stakeholder.
Phone: Decode string, e.g. input “3[a2[c]]” output “accaccacc” What if the string is a stream that is not able to fit into the memory? Onsite: LRU Cache Implement KNN, bias variance tradeoff, why curse of dimensionality, discussion of convergence of sgd (or gd), why cross validation Min height tree
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