LinkedIn Machine Learning Engineer Interview Questions
12+ LinkedIn Machine Learning Engineer interview questions drawn from real candidate reports. Sources include 1Point3Acres, Blind, Glassdoor, Reddit, and LeetCode. Questions span every stage of the LinkedIn Machine Learning Engineer loop: OA, phone screen, system design, behavioral, and onsite coding.
What to Expect in the LinkedIn Machine Learning Engineer Interview
The LinkedIn 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.
LinkedIn Machine Learning Engineer Questions (Sample)
ZScaler | Senior ML Engineer Role | Bangalore | March 2024 | Offer
Current Status: Position: Lead ML Engineer at Informatica Location: Bangalore Total YOE: 7.5 Recruiter reached out to me after I applied via LinkedIn Hacker Rank Online Assesment Test: First was a 90 minute hackerrank online assesment...
LinkedIn | Phone Screen | MLE | US
I recently had a phone screen. Got two questions: Question: N robots on a line. Find a point such that the total distance traveled by all robots is minimized. Input: The position pi...
LinkedIn Senior AI engineer, Bay Area (Rejected)
I have 6.5 years of experiewnce in ML First technical round went well. One coding question and some design questions. Dont remember the exact question but it was something like a...
LinkedIn AI Engineer
Initial screening interview (couple months back) \t- sample from multinomial array n numbers, e.g [0.5, 0.25, 0.25] \t\t- Came up with solution that uses binary search, didn\'t manage to code...
Linkedin | Senior Software Engineer (AI/ML) | Seattle | Jan 2022 [Declined]
Status: 2.5 years experience Position: SDE2 at a top tech company Location: Seattle Linkedin onsite: ML round-1: Open-ended problem around a Linkedin product. Lots of discussion around feature engineering. Took me a while to just...
LinkedIn | ML Engineer | Accepted
I have infinite appreciation on Leetcode community and now that I signed a contract from LinkedIn, I want to give back as much as I can. I\'m afraid I can\'t...
Tiger Analytics | Analyst, Data Scientist | Virtual | Sept 2021-July 2022 [Rejected]
Status: 2020 Grad , Normal Private College (Tier 3/4) Company at that time : Tata Power Ltd Company Name: Tiger Analytics Position they offer: Data Scientist-1 Location: Banglore, INDIA Date: Apr, 2021 Applied Thorugh : Linkedin...
Cars24 | Data Scientist | Mumbai | Feb 2022 [Rejected]
Status: 2020 Grad , Normal Private College (Tier 3/4) Current Company : Tata Power Ltd (Lead Engineer) Company Interviewing: Cars24 Position they offer: Data Scientist Location: Mumbai, INDIA Date: Feb, 2022 Applied Thorugh : Referral Rounds 1) Home...
Cohesity | MTS- III | Bengaluru | Oct 2021 [Offer]
Status: 3.5 YOE , Mtech from Tier - 1 Position: SSE at MNC Location: Bengaluru Date: Oct 2021 Round 1 Coding : Design a linear data structure where elements are inserted, deleted , get...
LinkedIn | ML Software Engineer | Phone Screen [Pass]
Phone screen was split into three components with a current ML Software Engineer. First part was just introductions and backgrounds for both interviewer and candidate. The second component, involved a...
LinkedIn | ML Engineer | Sunnyvale | Nov 2019 [No offer]
Phone round: - Implement rand07 using rand01 - Implement unbiased rand01 from biased rand01 - Implement randxy (random number in the range x - y inclusive) - ML basics: logistic regression, neural nets, gradient...
Linkedin | Staff Software Engineer | Sunnyvale, CA [Reject]
Status: Working as Senior Staff/Principal Software Engineer in SFO. Position: Staff Software Engineer Location: Sunnyvale, CA ### Phone Interviews: Staff/Background Interview: (60 mins) 10 mins - Quick intro on interviewer Topics: Leadership: Roles of SE and SSE...
Difficulty Breakdown
7
easy
2
hard
Based on 12 questions with difficulty labels from candidate reports.
Interview Rounds
Here is how the LinkedIn Machine Learning Engineer questions in the LeakCode database break down by interview round, based on what candidates reported:
| Round | Questions in Database |
|---|---|
| phone screen | 7 |
| recruiter | 2 |
| system design | 1 |
| oa | 1 |
| manager | 1 |
Most Common Topics
Question Recency
3
2024
5
2022
Question counts by interview year, based on candidate-reported dates.
How to Prepare for the LinkedIn 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 LinkedIn Machine Learning Engineer questions are in the database?
12+ 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 LinkedIn 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 LinkedIn OA questions specifically?
Yes. The database includes online assessment questions tagged with round type. See the LinkedIn OA page for a dedicated view.
Related: LinkedIn All Questions · LinkedIn OA Questions · Browse All Companies · Data Sources