I applied online. The process took 6 weeks.
Very well-defined, clear, and fair process for the participants. Congratulations to the team who organized it. Before each stage, a PDF is provided describing exactly how the interviews work and what is expected in them. In this sense, I felt comfortable throughout the entire process regarding information on how it works, and I also felt super welcomed by the interviewers. Overall, the process applied to me was divided into 3 stages, the first with just one call, and the other two with two calls, scheduled on different days, but 60 minutes each: 1: HR Screening to talk about the company, the position, and understand my profile 2: Programming case + Architecture case The programming case was a pair programming session on HackerRank, with LeetCode Easy level exercises.
I would recommend studying more basic structures like lists/dictionaries and not focusing too much on concepts of more complex data structures like linked lists and binary trees, since the pair exercises don't demand that much. Studying around 50 LeetCode Easy exercises in my case was already enough to put me at a very comfortable level for this test. (Note: This recommendation is also given in the stage's PDF, so you can understand how well-organized the selection process is) As for the architecture case, it was a chat about the design of a system to solve a business problem.
In the beginning, the business context was well presented, and as the conversation developed, we ended up getting into more technical subjects related not only to ML model design, but also to the infrastructure part related to this type of implementation. Anyone with a bit of market experience in this area will breeze through it. I also think it's interesting that there was no whiteboard moment like is common in FAANGs and the like; it was more of a very relaxed chat, I really liked it 3: MLE case + Manager interview In this stage, I did an interview where a small business context was given in code format, and then it was necessary to understand this context and implement some features.
Nothing overly complex, and in my opinion, very consistent with what I imagine day-to-day work is like. In addition, I had an interview with the manager to understand the more specific challenge of the area. Since Nubank is a very large company, there is a huge breadth of subjects across the teams you could join. This is the moment for you to understand if you like the proposal/challenge of the area you will be entering and if it matches you And finally, I had some conversations with the HR team to finalize the offer. Overall, I evaluate the process as excellent, by far the best selection process I've ever done in my life.
Even though it took a considerable amount of time (+/- 6 weeks), I felt comfortable with the level of information I had during my procedure in the process, and I also felt super at ease during the interview evaluations. If I had to give a tip to anyone trying the process now, I would say to be patient in all stages, and explain your reasoning, especially in the live codings. In this type of interview, the main objective is to evaluate how you handle these challenges, and the most important thing is for you to be able to communicate well.
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The following metrics were computed from 3 interview experiences for the Nubank Machine Learning Engineer role in São Paulo, São Paulo.
Nubank's interview process for their Engenheiro De Machine Learning roles in São Paulo, São Paulo is fairly selective, failing a large portion of engineers who go through it.
Candidates reported having very good feelings for Nubank's Machine Learning Engineer interview process in São Paulo, São Paulo.