Taro Logo

Staff Machine Learning Engineer Interview Experience

June 1, 2023
Positive ExperienceGot Offer

Process

Standard hiring process:

  • Initial screen
  • Two tech screens, including one with code. This was not pure LeetCode, which was a nice surprise and enabled more discussion.
  • Hiring manager screen: half questions (e.g., "How would you do X?") and half discussion.
  • Virtual on-site: Multiple design interviews focusing on different areas of an ML product and pipeline, as well as behavioral and cross-team collaboration. This comprised about five rounds.

Difficulty is hard to gauge. I have enough ML industry experience to navigate the questions with some initial answers based on projects I led in the past. There were a couple of hard questions around MLOps.

Questions

(Coding) Write an API and data structure for a specific use case. How would you test it? What's the complexity of the different operations?

What's your experience with feature engineering? In hindsight, how would you do it differently and why?

What's your experience interacting with product teams or managers?

Was this helpful?

Interview Statistics

The following metrics were computed from 1 interview experience for the Affinity Staff Machine Learning Engineer role in United States.

Success Rate

100%
Pass Rate

Affinity's interview process for their Staff Machine Learning Engineer roles in the United States is incredibly easy as the vast majority of engineers get an offer after going through it.

Experience Rating

Positive100%
Neutral0%
Negative0%

Candidates reported having very good feelings for Affinity's Staff Machine Learning Engineer interview process in United States.

Affinity Work Experiences