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Now that I've started hiring AI engineers myself I have a different perspective on what ai engineers need to know to perform well in interviews. Here are some additional AI engineer interview questions, answers and tips for you to prep for your next interview. Make sure to watch the first video (it's quite popular :) https://youtu.be/leXRiJ5TuQo Need career advice, a mock interview or resume review for an AI engineer role? Work with me 1:1: https://clankerengineer.io/book My #1 AI tool: https://ref.wisprflow.ai/gustaf Sign up for my newsletter where I share what I learn as a senior AI engineer: https://the-human-loop.beehiiv.com/ Watch next: https://youtu.be/6QY30Y9lLd0 Connect with me: https://x.com/gostak_dd (Let me know you came from this video!) AI Engineer Interview Questions: - How do LLMs work? - How do transformers work? - How would you design an AI workflow to remove all dead links for hundreds of client websites? - How do you handle race conditions in your code? - How does concurrency work in Python? - Problems you can run into with asynchronous programming (asyncio) - How would you handle real-time versus batch processing for data updates? When is one preferred over the other? - How would you ingest and process different types of data: structured (SKUs), unstructured (reviews/FAQs), and user interaction data (logs)? - How do you ensure the quality of data that an LLM interacts with? - How would you generate and store embeddings for products and queries in a chatbot application? Best practices for generating and storing embeddings - How to prevent LLM hallucinations - How to handle exceptions in LLM/GenAI applications - How to reduce latency in GenAI applications like chatbots - How to reduce costs in GenAI applications - How to improve retrieval accuracy in GenAI applications

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