Mock Interviews

Interview Flow

1. Introduction (2 min): Tell me about yourself
2. ML Theory (15 min): Bias-variance, regularization, attention mechanism
3. Coding (20 min): Implement a mini neural network / data pipeline
4. System Design (15 min): Design a recommendation system
5. Behavioral (8 min): Tell me about a challenging ML project

Sample Questions

• "Explain the transformer self-attention mechanism. Write the attention formula."
• "Implement k-fold cross validation from scratch in Python."
• "Design a content moderation system that scales to 1B posts/day."

Interview Flow

1. Introduction (2 min): Background and experience
2. Python Concepts (10 min): GIL, decorators, generators, memory
3. Coding Round 1 (15 min): Data structures problem
4. Coding Round 2 (10 min): Design a Python class/module
5. Discussion (8 min): Testing, best practices, project deep-dive

Sample Questions

• "What's the output of this code?" (closure + mutable default trap)
• "Implement an LRU cache with O(1) get and put operations."
• "Design a rate limiter class with sliding window algorithm."

Interview Flow

1. Culture Fit (5 min): Why startups? How do you handle ambiguity?
2. Take-home Review (15 min): Walk through your submitted assignment
3. Live Coding (15 min): Build a feature end-to-end
4. Product Thinking (10 min): How would you approach building X?

Sample Questions

• "We have 10K users. Design an MVP for a feature — what's the fastest path?"
• "How would you prioritize between model accuracy and shipping speed?"
• "Build a simple REST API endpoint that does X in 15 minutes."