Post by Bhavay Mittal
Data Scientist @ Adobe | GenAI, RAG & LLM Systems in Production | NLP ā¢ MLOps ā¢ Azure/AWS | MSc Data Science | Open to Senior DS / Applied Scientist roles| Bangalore
AI Engineering interviews are brutal. The gap between building a model in a Jupyter Notebook and passing a production-level system design round is massive. Recently, I sat in the hot seat myself for a live Data Science mock interview on Karthik's channel (Think in Models). We deep-dived into real-world EDA, scaling distributions, and the critical balance between technical execution and business logic. You can watch my session here to see exactly what I mean: https://lnkd.in/gVcqYW8H The feedback I received from that session was invaluable. Experiencing that pressure in a mock environment is exactly what bridges the gap from a nervous candidate to a hired engineer. Now, I want to bring that same experience to you. I am officially taking applications for the AI Engineering Mock Interview Series on my podcast channel. I am looking for students, freshers, and professionals pivoting into AI/Data Science who want to test their skills in a realistic, zero-judgment environment. What we will cover in your session: Live Technical Scenarios: Core ML fundamentals, RAG architectures, and handling deployment bottlenecks. The "Invisible Layer": How you communicate your thought process and map technical decisions back to business value. Actionable Feedback: We will break down where you excelled and exactly what you need to tighten up before your real interview loops. If you are preparing for the upcoming placement season and want to bulletproof your interview strategy, let's get you ready. š How to Apply: If you want to participate in this series, send an email to [email protected] with your resume attached. Tag a friend or classmate in the comments who is prepping for their AI/Data Science interviews right now! #AIEngineering #DataScience #MachineLearning #InterviewPrep #TechCareers #MLOps