
Scale Research Engineer Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 8 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Scale.
Research Engineer
The interview process was pretty ad hoc, with ML questions that required coding. You'd really only be able to answer them if you'd studied the ML topic beforehand. The EM and engineers I spoke with seemed pretty new to the field, most just a couple of years out of grad school. It made me wonder about the team's experience level, given how early in their careers everyone is.
- Debug Torch (easy)
- Code a specific deep learning technique from a research paper (requires prior knowledge of the topic)
Machine Learning Research Engineer
For those valuing their time in the application process, the interview at Scale is a masterclass in efficiency!!! The company's computer vision assessment poses problems: Ambiguity: No clear criteria leaves applicants guessing about expectations. Bias and Inconsistency: Lack of standardized evaluation can lead to subjective judgments. Arbitrary Decision Making: Applicants can be rejected on undisclosed standards, compromising fairness and transparency.
- A computer vision detection task.
Machine Learning Research Engineer
I went through the whole 3 stages. First, a take home assessment where I picked CV. Then a 45 min technical phone screen. Finally, a virtual onsite that included SWE, ML, and behavioral stuff. The people were really chill and easy to talk to. They responded fast and I didn't have to wait long for their decision.
- Can you complete a take-home assessment on CV or NLP?
- Are you able to answer technical phone screen questions similar to what others have faced?
- Can you discuss SWE, ML, and behavioral topics during the onsite interview?
Scale Research Engineer Interview Questions
Quoted word for word from Scale interview reports.
“Can you retrieve the samples that were misclassified from the test dataset?”
Read reports →“How do you evaluate model performance?”
Read reports →“Could you show how to implement recent LLM sampling techniques?”
Read reports →“What are some basic data processing techniques?”
Read reports →“Can you code basic ML pipelines?”
Read report →“Can you complete a take-home assessment on CV or NLP?”
Read report →“Can you discuss SWE, ML, and behavioral topics during the onsite interview?”
Read report →“Are you familiar with the content on your resume and your research?”
Read report →“Are you able to answer technical phone screen questions similar to what others have faced?”
Read report →Formats, difficulty and experience
Across all 8 Scale interview reports.