Overall, I enjoyed the process. It was very transparent, I was given all the information needed to get prepared for each step. Unlike most of the companies that reject a candidate by email without any feedback, I was given a call by the recruiter who took the time to explain what the team liked and did not like about my profile. The feedback was constructive and I found the decision quite fair although I am upset. I applied on the company website. The interview process started with a call from a recruiter to discuss the position, my background, my expectations, and the overall interview process. The first step of the interview is a 1-hour textbook question with two employees from Onfido. The questions cover four main categories: probability, statistics, machine learning, and deep learning. The next step, if the previous one is successful, is the panel interview consisting of 5 rounds interview with 5 different people from Onfido. Each round is 1 hour long, and there is 1 hour break between each round. - For the first two rounds, I had to solve one leet code-like coding exercise for each. -The next round is the applied deep learning interview in which I presented a deep learning paper of my choice. I also presented a previous project I worked on. This round is closed with some practical questions about training and using deep learning. -Next comes the ML and DL fundamental interview. This interview is about answering textbook questions on ML, DL, and Maths (statistics, probabilities, calculus) using a whiteboard. -The last round is about chipping and monitoring ML and DL systems in production and how to work alongside ML engineers and MLOps. I did the whole process remotely.