5 stage interview: 1st stage - call with recruiter, discussion of my experience/CV etc 2nd stage - ML/Data Science interview: This was split into two parts. The first was a series of short fire questions on Machine Learning ("Explain correlation and covariance" etc). The second was a longer system design question where I walked through training and deployment of a hypothetical ML model. 3rd stage - MLE interview: This was also split into two parts. The first was a series of short fire questions on Python and MLE ("What are generators are and how they differ from normal functions?", "How would you send off multiple API requests as quickly as possible?" etc). The second was a longer system design question where I walked the through productionisation of an ML model. 4th and 5th stage were soft skills interviews. Overall a pretty positive experience. Quite a lot of stages, however on the plus side there was no take-home task (time consuming) or live coding (often not representative of the type or format of work that people actually do.)

Interview process consisted of 5 interviews, one HR screen, two technical interviews, one cross-functional and one with the hiring manager/leadership. All interviews were interesting and insightful. The technical interviews were non-coding, mainly quick-fire ML and Python & Kubernetes-related questions as well as previous project experience and design choices.