Behavioral: Turning Around Work That Was Failing, and a Time You Were the Blocker
Company: LinkedIn
Role: Machine Learning Engineer
Category: Behavioral & Leadership
Difficulty: medium
Interview Round: Technical Screen
In the behavioral section of a technical screen for a Staff machine learning engineer role, the interviewer asked two questions. Answer each with a specific story from your own work.
### Clarifying Questions
- What kind of failure counts for the first question: a project slipping, a model missing its target, a launch going wrong, or a production incident?
- At Staff level, should the stories show impact beyond your own team, for example across organizations?
- How long should each answer run before the interviewer starts asking follow-up questions?
### Part 1 — Turning a failure around
"Tell me about a time when you saved a failure from your work."
Describe something that was failing, or about to fail, and how you turned it around.
```hint Find the turning point
Choose a story in which you can name when and how you noticed the failure, and the specific decision of yours that changed its course.
```
#### What This Part Should Cover
- The stakes, and the signal that showed things were failing
- The candidate's own actions and decisions, separated from the team's
- A measurable result, and what changed afterwards so the failure would not repeat
### Part 2 — A time you were the blocker
"Tell me about a time when you were the blocker."
```hint Ownership first
Either way the prompt is read, the interviewer is probing self-awareness: how you realized your part in the delay or the stop, and how you treated the people waiting on you.
```
#### Clarifying Questions for this Part
- Does the interviewer mean a time you were the bottleneck holding up other people's work, or a time you deliberately blocked something, such as a launch or a design, that you believed should not go ahead?
#### What This Part Should Cover
- An honest account of how the candidate became the blocker, without blaming others
- How the candidate unblocked others, or justified and resolved a deliberate block, including communication with the people affected
- What the candidate changed in their own way of working afterwards
### What a Strong Answer Covers
- Two distinct, specific stories in a clear situation, task, action and result structure, each with the candidate's own decisions and quantified results
- Staff-level scope: influence across teams or organizations, not only individual execution
- Candor about the candidate's own mistakes, especially in Part 2, with lessons that changed behavior
- Concise delivery that leaves room for the interviewer's follow-up questions
### Follow-up Questions
- In the first story, what would have happened if you had not stepped in, and why had nobody else caught it?
- How did you keep stakeholders informed while the outcome was still uncertain?
- In the blocker story, how did the people waiting on you see the situation, and how do you know?
- What do you do now to notice early that you are becoming a bottleneck?
Overview: Two behavioral prompts from a Staff machine learning engineer screen: describe a time you turned around work that was failing, and a time you were the blocker. They test ownership, measurable impact, influence across teams and honest self-assessment, delivered as structured stories.