I was asked questions about my project. What I liked about this approach is that I was not being tested for specific knowledge that I may or may not have acquired, but rather for how I approach things and my ability to work with the team. It was very useful for me to get an idea of how it would be to work at Clarity AI.
About the projects you have worked
Describe the key steps for building a two-class predictive model, from initial problem definition, to the release of the model. For each step describe possible challenges or mistakes that may happen at that stage and how it may impact the final outcome
Question regarding RAG pipeline, Agent framework, DSA and system design
Classical ML - what is homoscedasticity? What is regularization Difference between Standardization and Normalization Linear regression and any 5 evaluation metrics Machine Learning pipeline
Github: Difference between Merge and Rebase
Python: what is context manager? What are decorators?
Lots of SQL work and light python work. No major questions about machine learning. I think that that's where they want to be soon, but they're just not there yet.
Pricing and Market entry questions.
Describe a good impactful project
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