Cleo (United Kingdom) Machine Learning Engineer Interview Questions
& Process

The interview process involved an initial call with the recruiter, followed by a technical ML interview, a system design/ML reasoning interview, and finally a live Python and ML coding assessment. Throughout the process, the recruiter consistently provided updates, outlined upcoming stages, and shared general feedback after each round. Despite not receiving an offer, the organized structure and consistent communication made it a standout interview experience. The company emphasized its fast-paced nature, suggesting potential for rapid learning and impact, but also hinting at a high-pressure environment and possibly challenging work-life balance.

It was a three stage interview. First, a general chat with HR about basic stuff and my background. Second, more technical questions about my CV and work history. Third, a technical interview with senior engineers. This last one had two parts: first, a machine learning problem about data imbalance, and second, a Python coding task where I couldn't run or debug my code. The last stage felt a bit intense, and the interviewers weren't very helpful.

The whole process from applying to getting the offer took just under 4 weeks. First, there was a quick 15min chat with the internal talent partner who was super helpful and gave me lots of resources to understand the interview process better. Then came a 30min behavioural interview with two ML engineers, followed by a 60min technical interview and a final 30min interview with a manager. I got helpful feedback after each stage and found out the results within 3 days. It was a really efficient and smooth process, and the interviews themselves were actually interesting and made me think.