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UiPath interview notes, page 2 of 2

Large Enterprises

Most of these UiPath write-ups come from Machine Learning Engineers (14), then Software Engineers (6). The most reported rounds are the technical phone screen (15), the behavioral / leadership round (2), the system design round (2) and the multi-round onsite (1).

20 interview notes · updated Jul 2026

UiPath·Machine Learning Engineer·Technical Phone Screen

May 2026
Interviewed for an ML Engineer role at UiPath. The session mixed a resume walkthrough with a behavioral deep dive on ambiguity, which I wasn't fully prepared to tie together cleanly.
  • Walk me through your resume, focusing on the roles you've held, key projects, technologies you used, and any measurable impact you can point to.
  • Tell me about a specific situation where you faced significant ambiguity at work. What was unclear, how did you reduce that uncertainty, what trade-offs did you weigh, and what happened in the end?
  • What frameworks or habits do you rely on to manage ambiguity in ongoing projects, not just one-off situations?

“I rambled a bit on the earlier roles and spent too long on a project that wasn't even that relevant.”

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UiPath·Machine Learning Engineer·Technical Phone Screen

May 2026
Interviewed for an ML Engineer role at UiPath, technical phone screen focused on deep learning fundamentals. One question but it went pretty deep, they weren't satisfied with a surface-level answer.
  • Can you explain how dropout works in deep neural networks and why it's effective as a regularization technique?

“I started with the basic mechanic (randomly zeroing neuron outputs during training) and thought that'd be enough, but they kept pushing.”

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UiPath·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Interviewed for an ML Engineer role at UiPath, got a technical phone screen with some CS fundamentals thrown in. Nothing too wild but they did push on complexity analysis more than I expected.
  • What are the time complexities for insertion and deletion in a hashmap, and what factors affect them?

“I gave the O(1) average answer pretty quickly and thought I was done.”

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UiPath·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at UiPath focused entirely on the database layer of a project, which I wasn't expecting to go that deep on. They really wanted you to own every decision, not just describe what you built.
  • Walk through the database design for a project you worked on: what were the business and performance goals, what data model and access patterns did you design for, and which datastore did you choose and why?
  • How did you evaluate the trade-offs between cost, latency, throughput, and availability when making your database decisions?
  • When you talk about consistency in your database queries, what exactly do you mean? Define it precisely and explain how it affects the read and write paths and what users actually observe.
  • Did you complete the database-related tasks in the project, and how did you validate that the solution met the goals?

“I talked through a project where we used DynamoDB and I felt pretty good about explaining the access patterns and partition key choices.”

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UiPath·Machine Learning Engineer·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at UiPath for an ML Engineer role, basically one big ambiguity question dressed up with a lot of sub-parts.
  • Tell me about a time when project requirements were unclear or kept shifting. How did you figure out what success looked like, who the right stakeholders were, and how to reduce uncertainty? What did you prioritize first, what trade-offs did you make, and how did you communicate those decisions?

“This question has like five questions inside it and I didn't realize that until I was already two minutes into my answer.”

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UiPath·Software Engineer·Technical Phone Screen

Jun 2026
UiPath software engineer interview with a coding question that had a few layers to it. Started straightforward enough but kept expanding into streaming and Unicode territory which I wasn't fully ready for.
  • Given a string, find the length of the longest substring with no repeated characters, where letter casing is ignored (so 'A' and 'a' count as the same). All ASCII characters including whitespace are valid. Explain your algorithm's time and space complexity, cover edge cases like empty strings or all-duplicate inputs, and describe how you'd handle Unicode. Then, for inputs too large to fit in memory, walk through a streaming approach and its trade-offs.

“Sliding window with a set, got that part out pretty quickly.”

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UiPath·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Interviewed for an ML Engineer role at UiPath and got a coding question that felt more like a software engineering screen than anything ML-related. Classic string problem, but they wanted me to walk through multiple approaches and complexity tradeoffs, which I wasn't fully prepared for.
  • Given an array of strings, write a function that finds the longest common prefix shared by all strings. Return an empty string if none exists.

“I jumped straight to the vertical scan approach (compare character by character across all strings at the same index) which works fine, but then they asked me to walk through other ways to do it.”

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UiPath·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Got a coding round at UiPath for an ML Engineer role and they threw a pure algorithms problem at me, which I wasn't really expecting. It was a knight-moves-on-infinite-grid variant and the scale of the coordinates meant BFS alone would've been a disaster.
  • On an infinite 2D grid, a piece moves in L-shapes (like a chess knight). Given a target coordinate where each axis can be up to 1 billion in magnitude, write a function that returns the minimum number of moves to reach that target from the origin. You must exploit symmetry, handle edge cases, and explain your algorithm with complexity analysis.

“My first instinct was BFS and I even started writing it out before realizing coordinates go up to 1e9.”

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UiPath·Machine Learning Engineer·Technical Phone Screen

Jul 2026
Interviewed for an ML Engineer role at UiPath and got a probability question that felt more like a stats refresher than anything ML-specific. Pretty straightforward if you remember your independence rules.
  • You roll two fair six-sided dice twice (four total die rolls). What is the probability that all four outcomes are even?

“Each die has a 1/2 shot at landing even, and since the rolls don't affect each other, you just multiply (1/2) four times and get 1/16.”

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UiPath·Machine Learning Engineer·Technical Phone Screen

Jul 2026
UiPath ML Engineer interview, technical phone screen focused on ML fundamentals. The loss function question was the centerpiece and went deeper than I expected.
  • What loss function would you use for a regression model, and how do the common options compare in terms of robustness, gradient behavior, and noise assumptions?

“I started with MSE and MAE which was fine, but the follow-up about noise assumptions is where I got a bit shaky.”

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