Scale AI Software Engineer interview questions

48 Software Engineers have shared notes from their Scale AI interviews, with the questions they were asked in each round. That is 61% of the 79 Scale AI interview notes on Screna AI.

48 Software Engineer interview notes

Scale AI·Software Engineer·Take-home Assignment

Jul 2026
Scale.ai gave me a take-home style coding exercise where they handed over a multi-file project and asked me to find and fix bugs in it. The setup was more involved than I expected, lots of files, CSV inputs, and you have to actually run the thing and poke around with print statements to find what's broken.
  • You're given a multi-file codebase with CSV inputs. The interviewer walks you through the high-level logic, then you have to read the code, run it, and use print statements to find a bug where an off-by-one error in a headcount capacity check lets one too many people get assigned to a project. Find the file and line, explain the issue, and fix it.

“The bug itself wasn't that hard once I actually ran the code and added some prints around the assignment loop.”

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Scale AI·Software Engineer·Onsite - System Design / Architecture

Jul 2026
Scale.ai system design round for a Forward Deployed Engineer role, one hour, one question about designing a task quality review system. Pretty open-ended and I wasn't totally sure how deep to go on the ops side versus the technical architecture.
  • Design a task quality review system.

“This fits Scale pretty naturally given what they do, so I expected it, but I still fumbled the scoping a bit early on.”

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Scale AI·Software Engineer·Onsite - Behavioral / Leadership

Jul 2026
Behavioral round at Scale AI for a software engineer role, just one question but they really wanted you to dig into the mechanics of how you learn under pressure, not just the outcome.
  • Tell me about a time you had to pick up something new very fast to keep a project on track. Walk me through how you approached it and what actually happened.

“I structured my answer as situation, action, result and it felt pretty solid in the moment, but looking back I spent way too long on the context and rushed the part about what I actually did to learn.”

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Scale AI·Software Engineer·Technical Phone Screen

Jul 2026
Scale.ai SWE coding round, pretty standard data structures stuff. One question on a task scheduler implementation that was more straightforward than it sounds once you figure out the right structure.
  • Implement a TaskScheduler class with an AddTasks method that accepts a list of tasks (each with an id, deadline, and subtasks field) and a ConsumeTask method that pops and returns the task with the earliest deadline. If the scheduler is empty, return the string 'no task'.

“I went straight to a min-heap keyed on the deadline field and they seemed fine with that.”

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Scale AI·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Scale AI for a software engineering role, just one conflict-resolution question but they clearly cared a lot about how you handle disagreement without blowing things up.
  • Tell me about a time you had a conflict with a teammate, stakeholder, or manager. What caused it, how did you handle it, and what happened in the end?

“I structured my answer as situation, action, result and it felt pretty natural, but I spent too long on the backstory and rushed the actual resolution part.”

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Scale AI·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Scale.ai system design round for a software engineer role, one big open-ended question about building a task scheduler from scratch. Took up the whole session and went pretty deep into territory I wasn't fully prepared for.
  • Design a task-scheduler service where each task has an id, a deadline, and a list of prerequisite task ids. Clients can add tasks and consume the next runnable task with the earliest deadline. Walk through validation, cycle detection, concurrency, and handling a continuous stream of incoming tasks.

“This question sprawled in a way I didn't anticipate.”

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Scale AI·Software Engineer·Technical Phone Screen

Jun 2026
Scale.ai debugging round for a Software Engineer role, this one focused on fixing a sort bug in a project assignment feature. Pretty targeted exercise, just one bug to track down and fix, but the details mattered.
  • You're given code where projects are being sorted in ascending priority order, but the system should process higher-priority projects first. Find the sort logic and fix it so the ordering is correct.

“The fix itself is small, like a one-line comparator flip, but I spent more time than I should've re-reading the surrounding code to make sure I wasn't missing some intentional design choice.”

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Scale AI·Software Engineer·Technical Phone Screen

Jun 2026
Scale.ai software engineering interview that went deep on testing philosophy. One question, but it had a lot of surface area and I felt like I was winging parts of it.
  • Design a unit test suite for a non-trivial piece of production code. Walk through what cases you'd cover, how you'd isolate the unit under test, what you'd assert on, how you'd deal with non-determinism, and how you'd measure whether the tests are actually good.

“This felt manageable at first and then kind of sprawled.”

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Scale AI·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Scale AI system design round for a software engineer role. The whole thing was one big open-ended question about building a load balancer in Python, and they wanted you to go deep on basically every layer of the system.
  • Design a lightweight load balancer for a Python backend that dispatches tasks to a pool of worker processes. Cover worker state machines, priority-based task dispatching, dynamic scaling, timeout handling, and how you'd structure the core classes and concurrency model.

“This question is massive.”

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Scale AI·Software Engineer·Technical Phone Screen

Jun 2026
Scale AI SWE interview with a pretty involved coding/design question about interval merging and geospatial joins. Not a LeetCode grind session, more like a systems-thinking problem dressed up as code. Walked away feeling like I did okay on part (a) but fumbled the complexity justification for part (b).
  • You have two in-memory datasets: one with party time windows (partyId, startTime, endTime in ISO-8601 UTC) and one with geographic data (partyId, state, county, town, community). Write a method that joins them on partyId and returns, for each community, the earliest party start time and the latest party end time. Specify your return type and how you handle output ordering.
  • Using the same two datasets, compute for each town the total number of hours during which no party is happening anywhere in that town. Merge overlapping or adjacent intervals first (where adjacent means endTime equals the next startTime, which should not count as a gap), then sum the gap durations strictly between merged intervals over the span from earliest start to latest end in that town. Return a Map from town to hours, using UTC and ignoring DST. State your rounding policy and justify time and space complexity.

“This part felt manageable.”

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