Process
The interview process consists of three rounds:
1st Round: Machine Learning and Statistics questions.
2nd Round: Machine Learning, Statistics, and coding in Python or SQL. There are typically 1 or 2 SQL questions at most, with more emphasis on Python.
3rd Round (On-site): Machine Learning, Business Acumen, Coding, and Behavioral questions.
Questions
Q: Explain the difference between boosting and bagging.
Q: How do LSTMs solve the vanishing gradient descent problem?
Was this helpful?
Interview Statistics
The following metrics were computed from 1 interview experience for the PayPal Machine Learning role in United States.
Success Rate
PayPal's interview process for their Machine Learning roles in the United States is incredibly easy as the vast majority of engineers get an offer after going through it.
Experience Rating
Candidates reported having very good feelings for PayPal's Machine Learning interview process in United States.
PayPal Work Experiences
- 3.0Salary before layoffsSenior Software Engineer • Former EmployeeSan Jose, California, United StatesMarch 12, 2024Pros: Decent tech stack and internal tools.Cons: WLB is a hit or miss based on team.
- 5.0Loved My Internship Experience!SWE Intern • Current EmployeeChicago, Illinois, United StatesSeptember 6, 2023Pros: Very friendly! Great environment for me!Cons: None! It was great for me.
- 4.0Smart Team, Too SlowSolutions Architect • Current EmployeeBengaluru, Karnataka, IndiaAugust 4, 2019Pros: Open working environment, smart colleagues, and a clear vision for the company.Cons: Too big to be agile
PayPal Interview Questions
