I was asked a series of questions ranging from leadership topics to more detailed engineering and data science questions. For example, was asked for specifics (but not low-level details) on how some machine learning algorithms worked, to test my breadth and depth of knowledge.
Scenario based questions, TDD approach, how to write parseInt checking coding approach with all test scenarios covered.
Closest thing to a "coding" interview was a few mock PRs in the language required for the role. We went through a few different approaches to solving a particular problem and discussed the bottlenecks and potential pitfalls of each, with a focus on concurrency.
Technical questions with efficacy datasets
* How Kafka broker partition leader election happens? * Consumer rebalancing upon addition and removal * Consumer groups * Partition additions * Cross data center replication * Master/Master setup etc
Zig zag traversal of Binary Tree Snake and Ladder Explain MLOps framework
Walk me through your background and how your experience would fit for this role.
1. What kind of mitigations you have made, when you can't achieve the target timeline for a project delivery from QA perspective? 2. What kind of challenging project deliverables you made, even your company is help you in the execution.
How would you design/architect X?
Code review together, then try to fix code smell
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