Recently, I had the chance to interview for a GenAI Data Scientist role at a regional financial institution, focusing on chatbot applications. The interview was quite technical and could be broken down into three key segments - model development, model inference, and software engineering.

By the end of the session, I already had a good sense of where I fell short - my knowledge of LLMs. I haven’t actively developed models in a while, and definitely not since ChatGPT changed the landscape in 2022. So, when asked about topics like temperature, top-p, and top-k, I struggled to provide strong answers.

That said, I felt more confident in the other two areas. I had solid experience optimizing model inference and writing high-performance code. Still, I wasn’t as fast as I would have liked - something to work on.

Overall, it was a great learning experience. I walked away with a clearer picture of my gaps without even needing to ask for feedback. Time to level up! 🚀