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.
How optimization works in an ML model
What is my Greatest strength and weakness
What sort of questions do you ask Copilot or ChatGPT to optimize code or assess performance?
CNN mechanism, filters, pooling layers, Transformer mechanism, positional encoding
Some fundamental machine learning questions and then a deep dive into RAG system components.
Q: Describe yourself? Q: What project are you the most proud of?
General questions about supervised learning algorithms and technologies.
Q: SQL query Q: programming exercise Q: deep learning knowledges
What is the difference between a batch model and a streaming model?
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