Uber Machine Learning Engineer Interview Questions
13+ Uber Machine Learning Engineer interview questions drawn from real candidate reports. Sources include 1Point3Acres, Blind, Glassdoor, Reddit, and LeetCode. Questions span every stage of the Uber Machine Learning Engineer loop: OA, phone screen, system design, behavioral, and onsite coding.
What to Expect in the Uber Machine Learning Engineer Interview
The Uber Machine Learning Engineer interview process typically runs 4 to 6 rounds depending on seniority level. Based on candidate reports in the LeakCode database, the loop usually includes a resume review, an online assessment or coding phone screen, one or more technical rounds, a system design round (for senior and above), and a behavioral or values round.
Difficulty skews toward medium and hard LeetCode-style problems in the coding rounds. System design questions test breadth (component selection, scaling, trade-off reasoning) more than deep implementation. Behavioral questions are tied to the company's stated values and principles.
Uber Machine Learning Engineer Questions (Sample)
Uber New Grad | Depth in Specialization Interview (US) Android
Hi everyone, I was wondering if anyone here has gone through the Uber New Grad interview that focuses on “depth in specialization” in the US. What does this round usually look like? Is it more like: *
Machine Learning Engineer | Multiple Companies
Hi Folks, I have around 10 years of experience with 5 in DS/ML domain. Currenly, I am working in a leading consulting firm in DS/ML. Sharing the interview experience with the...
Uber | MLE (L4) | Bangalore | April 2024 | Rejected
Education : Non-CS (Tier 3) YOE: 1.10 Applied online via portal, got an email for next steps in ~2 weeks. 1. Technical Screening: -- Initial discussion around current experince and projects. -- Some modifications...
Uber Interview Experience For Data Scientist
Recently Uber came to our campus for the recruitment of Data Scientist role. According to the recruitment process there were in total 5 rounds. Each round was an eliminati...
Cricbuzz Interview Experience || SDE-1(Backend) || Rejected
Cricbuzz Interview Experience for SDE-1 Backend Current Role: SDE-1 (worked in backend, ML, and frontend). Years of Experience: 1 year 11 months I applied to Cricbuzz last year but didn\'t clear the first...
Quadeye | Full Stack Developer | Reject
Process: Recruiter Reached out to me on Linkedin. I am interested in a Full Stack Developer role. Online Test Three DSA questions 1. https://leetcode.com/problems/break-a-palindrome/ 2. Given an array representing n positions along...
Uber Intern 2022 || Selected || Oncampus
The 1st round was OA round, where I was able to solve 2 questions fully and the last question partially. It was an online round at the platform codesignal. I don\'t...
Uber Technical Phone Screen | Machine Learning Engineer role
Hi all, I am in the interview process for Machine Learning Engineer role at Uber - Toronto Canada. First round was CodeSignal assessment which I passed with a score of 839. Next...
Uber | SDE2(L4) | July - 2022 | Rejected
Status: 2019 Grad , one of the NIT Current Company : Job Ad tech company (SDE-2) Location: Banglore, India Date: July 2022 Applied Through : Got referral from an Engineering Director for Bengaluru Location Within...
Uber Phone Screen | US | Sr. MLE | Accept
I gave phone screen in Nov. 2021. I was asked this question 1) https://leetcode.com/problems/top-k-frequent-words/ The input was a long string containing several words. I presented solution with TC: O(NlogK) 2) What if special...
ML Coding: Logistic Regression from Scratch
Implement core pieces of binary **logistic regression** from scratch. 1. Given training data `X` (shape `n x d`) and labels `y` (0/1), implement: - Forward pass: `p = sigmoid(Xw + b)` - Loss: B
Uber ATG | L4 | SF [Reject]
I had two rounds with Uber ATG self driving team interview. Each round took an hour long. The interviewing process is tough. I have 5 mins to introduce myself and go...
Uber | SDE1 | SF | Oct 2019 [Offer]
2020 University Graduate: Software Engineer Applied: 6th September 2019 Reply back for phone screen: 18th September 2019 Phone screen: 30th Septemeber 2019. Alloted 45 min. Completed in 30 min. Phone screen: ------------ Interviewer talked about his...
Difficulty Breakdown
6
easy
2
medium
1
hard
Based on 13 questions with difficulty labels from candidate reports.
Interview Rounds
Here is how the Uber Machine Learning Engineer questions in the LeakCode database break down by interview round, based on what candidates reported:
| Round | Questions in Database |
|---|---|
| oa | 6 |
| phone screen | 3 |
| system design | 1 |
| recruiter | 1 |
| coding | 1 |
Most Common Topics
Question Recency
1
2026
3
2024
2
2023
3
2022
Question counts by interview year, based on candidate-reported dates.
How to Prepare for the Uber Machine Learning Engineer Interview
Use the LeakCode question database as your primary research tool. Filter by role (Machine Learning Engineer), then by round type to focus your prep on the specific stages in your upcoming loop. Sort by recency to see what 2026 candidates actually faced.
- Start with questions from the last 12 months. Interview processes change and recent data is the strongest signal.
- Cross-reference questions that appear in multiple sources (1p3a, Blind, Glassdoor). Multi-source confirmation means a question has stronger recurrence probability.
- For system design rounds: focus on the question patterns, not individual questions. The same design principles recur across many prompts.
- For behavioral rounds: map your experiences to the company's stated values before the interview. Most behavioral questions at top companies are derivatives of a small set of core leadership competencies.
FAQ
How many Uber Machine Learning Engineer questions are in the database?
13+ questions from verified candidate reports. The count grows as new reports are scraped daily from 1Point3Acres, Blind, Glassdoor, Reddit, and LeetCode.
Are these questions from real Uber interviews?
Yes. All questions are sourced from actual candidate interview reports, not generated by AI. Each entry links back to its source URL where available, and questions are tagged with the year and round reported by the candidate.
How current is this data?
LeakCode updates daily. The database is filtered to exclude duplicate and low-quality entries. You can filter by interview year to focus on recent cycles.
Does LeakCode cover Uber OA questions specifically?
Yes. The database includes online assessment questions tagged with round type. See the Uber OA page for a dedicated view.
Related: Uber All Questions · Uber OA Questions · Browse All Companies · Data Sources