Hiring Guide

Top 50 Generative AI Interview Questions and Answers

Ace your next Generative AI interview with this comprehensive guide covering transformer architectures, large language models, diffusion models, prompt engineering, fine-tuning strategies, and production deployment.

Core Concepts
Data Structures and Algorithms
System Design
Coding and Debugging
Behavioral Questions

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Core Concepts

Data Structures and Algorithms

System Design

Coding and Debugging

Behavioral Questions

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Top 50 Generative AI Interview Questions and Answers

Identify Top 5% Generative AI Talent

Core Concepts

Explain the self-attention mechanism in transformers and how it differs from traditional RNN attention.

What is the difference between autoregressive and non-autoregressive generation in language models?

Describe the architecture and training process of diffusion models like Stable Diffusion.

What are LoRA (Low-Rank Adaptation) and QLoRA, and when would you use them for fine-tuning LLMs?

Explain the concept of temperature and top-k/top-p sampling in text generation. How do they affect output quality?

What is the difference between RLHF (Reinforcement Learning from Human Feedback) and DPO (Direct Preference Optimization)?

Explain how Flash Attention optimizes the attention mechanism. What are the memory and speed improvements?

What are the key differences between encoder-only (BERT), decoder-only (GPT), and encoder-decoder (T5) transformer architectures?

Describe the challenges of inference optimization for large language models and common solutions like quantization and KV cache.

What is prompt engineering and what are advanced techniques like chain-of-thought, few-shot learning, and ReAct prompting?

Data Structures and Algorithms

Implement an LRU (Least Recently Used) Cache with O(1) time complexity for both get and put operations.

How do you find all pairs in an array that sum to a target value? What's the optimal approach?

Explain the sliding window technique and implement maximum sum of a subarray of size k.

What is the difference between a stack and a queue? Implement a queue using two stacks.

Explain time complexity of dictionary/hash map operations. When would they degrade to O(n)?

Implement a function to detect if a linked list has a cycle. What's the optimal space complexity?

What is a Trie data structure? Implement insertion and search operations.

Explain the difference between BFS and DFS. When would you choose one over the other?

Implement a min heap and explain its time complexity for insertion and extraction.

What is dynamic programming? Explain with the Fibonacci sequence and optimization from recursion to memoization to tabulation.

System Design

Design a scalable URL shortener service like bit.ly. What are the key components and how would you handle high traffic?

How would you design a real-time chat application supporting millions of concurrent users? Discuss the architecture, protocols, and data consistency challenges.

Design a distributed rate limiter that can handle 100K requests per second. How would you ensure accuracy and prevent race conditions?

Design a news feed system like Facebook or Twitter. How would you handle feed generation, ranking, and real-time updates at scale?

Design a distributed task scheduler that can execute millions of jobs with precise timing. How would you handle failures and ensure exactly-once execution?

Design a content delivery network (CDN) from scratch. What are the key challenges in cache invalidation, routing, and global distribution?

Design a distributed file storage system like Google Drive or Dropbox. How would you handle file synchronization, versioning, and conflict resolution?

Design a real-time collaborative document editing system like Google Docs. What algorithms and architecture would you use to handle concurrent edits?

Design a distributed search engine like Elasticsearch. How would you handle indexing, sharding, and query optimization for billions of documents?

Design a video streaming platform like Netflix or YouTube. How would you handle video encoding, adaptive bitrate streaming, and content delivery at global scale?

Coding and Debugging

Write a Python function to flatten a nested list of arbitrary depth without using external libraries.

Implement a function to check if a string is a palindrome, considering only alphanumeric characters and ignoring case.

How would you debug a memory leak in a Python application? What tools and techniques would you use?

Explain exception handling best practices. Write code demonstrating proper use of try-except-else-finally blocks.

What is monkey patching? Provide an example and discuss when it's appropriate to use.

Write a function to reverse a string in-place. Discuss why this is challenging in Python.

Demonstrate how to use Python's logging module for debugging in production environments.

Write a decorator that measures and logs the execution time of a function. Handle both sync and async functions.

Explain how to profile CPU and memory usage in Python. Provide code examples using cProfile and memory_profiler.

Write a function to detect and handle circular imports in Python. What strategies prevent circular import issues?

Behavioral Questions

Tell me about a time when you had to implement a generative AI solution under tight deadlines. How did you manage it?

Describe a situation where a generative AI model you deployed produced unexpected or biased outputs. How did you handle it?

Can you share an example of when you had to optimize the cost of running generative AI models in production?

Tell me about a time when you had to explain the limitations of generative AI to non-technical stakeholders who had unrealistic expectations.

Describe a challenging technical problem you faced while fine-tuning or customizing a large language model for your organization's specific use case.

Tell me about a time when you had to balance innovation with responsible AI practices in a generative AI project.

Share an experience where you had to troubleshoot and debug unexpected behavior in a generative AI system that was difficult to reproduce.

Describe a situation where you had to collaborate with cross-functional teams (data scientists, product managers, legal) on a generative AI initiative.

Tell me about a time when you had to make a difficult architectural decision for a generative AI system, such as build vs. buy or choosing between different model providers.

Describe an instance where you had to rapidly learn and implement a new generative AI technology or framework to solve a business problem.

Hire Pre-Vetted Generative AI Engineers

Interview Questions for Other Related Skills

Why Index.dev?

Our talent is hand-picked

We prioritize speed

We respect your budget

Top 50 Generative AI Interview Questions and Answers

Identify Top 5% Generative AI Talent

Core Concepts

Explain the self-attention mechanism in transformers and how it differs from traditional RNN attention.

What is the difference between autoregressive and non-autoregressive generation in language models?

Describe the architecture and training process of diffusion models like Stable Diffusion.

What are LoRA (Low-Rank Adaptation) and QLoRA, and when would you use them for fine-tuning LLMs?

Explain the concept of temperature and top-k/top-p sampling in text generation. How do they affect output quality?

What is the difference between RLHF (Reinforcement Learning from Human Feedback) and DPO (Direct Preference Optimization)?

Explain how Flash Attention optimizes the attention mechanism. What are the memory and speed improvements?

What are the key differences between encoder-only (BERT), decoder-only (GPT), and encoder-decoder (T5) transformer architectures?

Describe the challenges of inference optimization for large language models and common solutions like quantization and KV cache.

What is prompt engineering and what are advanced techniques like chain-of-thought, few-shot learning, and ReAct prompting?

Data Structures and Algorithms

Implement an LRU (Least Recently Used) Cache with O(1) time complexity for both get and put operations.

How do you find all pairs in an array that sum to a target value? What's the optimal approach?

Explain the sliding window technique and implement maximum sum of a subarray of size k.