Coactive AI Machine Learning Engineer interview questions

1. HR screening: The HR was super friendly, even had some technical knowledge to ask me about my past experiences, and remained available for the entire process to answer the questions I had. During this screening, I had to answer a few questions about ML fundamentals. The questions are pretty easy, they just want to make sure you know the basics. 2. Technical interview with the hiring manager: We went into details about the projects I worked on. 3. Live ML-focused Python coding interview 4. Onsite interviews: they flew me in to their head office in Silicon Valley, which was so cool! It was actually my first time in the US, it helped me gauge the culture and my future peers. I got the chance to meet a lot of the team during my lunch with them: the company is full of super cool and brilliant people. The onsite included an ML System Design interview, live DSA-focused Python coding interview, and a talk with the head of engineering. Both coding interviews were frankly not hard, they mostly try to evaluate your reasoning skills, your ability to justify your reasoning, and good coding practices. There were no irrelevant, LC hard type of questions, which I really appreciated. The ML System Design interview was harder, more open-ended. In the end, after meeting the people + being interested about the product + the competitive salary for the Montréal area, I accepted the offer.