Two technical rounds:
1st round: Feature engineering on an existing dataset. 2nd round: A coding problem.
Throughout, the questions were very specific to Affirm. The interviewers were very helpful and guided well. It didn't feel like coding up an arbitrary LeetCode problem, but seemed very close to what the actual job demanded.
Q: Given a dataset, set up a feature engineering pipeline.
Q: Given a list of strings, find the smallest unique substring for each string.
The following metrics were computed from 2 interview experiences for the Affirm Machine Learning Engineer role in San Francisco, California.
Affirm's interview process for their Machine Learning Engineer roles in San Francisco, California is extremely selective, failing the vast majority of engineers.
Candidates reported having mixed feelings for Affirm's Machine Learning Engineer interview process in San Francisco, California.