Me postulé en línea. El proceso tomó 1 semana. Acudí a una entrevista en Stripe
Entrevista
The technical interview was a pretty absurd format. They give you a dataset and you have 50 minutes to understand it, analyze it, develop a model for it, and assess the model for it. You do not have much time do things properly so it did not feel like an appropriate interview.
If you want to pass this interview, you will need to memorize the pandas and sci-kit learn APIs. While it is technically "open note", you cannot use a second monitor and you will probably be judged for having your own notes.
Interviewer also does not provide much guidance of what is expected of you and will just let you fumble around the problem while remaining silent.
Me postulé a través de una recomendación de un empleado. Acudí a una entrevista en Stripe (San Francisco, CA) en jun 2026
Entrevista
Pre-onsite step has two rounds. One is ML integration round. You need to work with a pre-loaded dataset, process the data and train a model. Another one is a programming problem with a few tasks. 2hrs in total.
Preguntas de entrevista [1]
Pregunta 1
Process the data and train a predictive model for the target. What is data normalization used for?
Online Assessment — The first round of interviews is scheduled to include both coding and machine learning problems. Overall, the process appears to follow a fairly standard interview procedure, beginning with technical assessment before moving into later-stage evaluations.
Me postulé a través de un reclutador. Acudí a una entrevista en Stripe en abr 2025
Entrevista
2 technical screens (coding, ml coding), onsite was 4 rounds (coding, debugging, system design, hiring manager). Coding questions were OOP and class oriented. Problems were practical, the ml coding round had a dataset provided and you had to build and evaluate a model in 1h.
Preguntas de entrevista [1]
Pregunta 1
system design had an emphasis on real time deployment