Meta Machine Learning Engineer Phone Screen Questions
22+ questions from real Meta Machine Learning Engineer Phone Screen rounds, reported by candidates who interviewed there.
What does the Meta Phone Screen round test?
The Meta phone screen typically lasts 45-60 minutes and evaluates core Machine Learning Engineer fundamentals. Candidates should expect 1-2 algorithmic problems, basic system design discussion at senior levels, and questions about relevant experience. The goal is to confirm technical competence before bringing candidates onsite.
Top Topics in This Round
Meta Machine Learning Engineer Phone Screen Questions
Facebook | E5 | July 2020 | Reject
Phone Interview: Odd Even jump kind of problem & an ML algorithm. Onsite: Coding1: Matrix rotation kind of problem, string matching. Coding 2 Bit manipulation, Sort the array by parity type...
Meta Software Enigneer - Initial Prescreen stage timeline
I recently interviewed for a Production Engineer (University Grad) role. After I was moved to the initial prescreen stage, I submitted the questionnaire within a couple of days and received an invitat
Meta Machine Learning Engineer Fulltime Tech Phone Screen Interview Experience
This post was last edited by yah007 on 2025-9-30 19:30 Coding: First Question: LeetCode Yi Si Si Bar Second Question: Similar to LeetCode Yi Ling Ling Si VO: Coding Round 1: LeetCode: Qi Er Yi Er, Sim
Meta MLE E4/E5 Pass/Fail
Hi, I recently completed my onsite at meta for MLE (E4/E5). Phone Screen Coding: 2 medium -- solved both problems with optimal solutions. Moved to onsite on the next day. Round 1 [coding] 2 medium...
Meta IC5 interview experience - Thoughts?
I recently completed the Meta interview loop for an IC5 Machine Learning role and would appreciate feedback on my performance, chances for the role, downleveling to IC4, or rejection. Here’s my backgr
Meta E4 Full Loop | Pass & Offer accepted
I completed the Meta E4 Full Loop for Software Engineer, Machine Learning and received an offer. Here you have the process: Phone screen - Coding challenge. Two medium questions from Leetcode Top...
Helping the community Q1. Implement cd. Given current working directory and argument move to final path E.g. cwd - /a/b/c arg - d Output - /a/b/c/d Missed one case while explaining the...
Meta SWE ML E5 | Onsite + Phone screen
Giving back to the community. # Phone screen Standard 2 questions 40 mins 1. https://leetcode.com/problems/kth-largest-element-in-an-array/description/ Asked should I do heap or quickselect. Interviewer asked me to explain how both of them work...
Meta | Research ML | USA
Phone Screen: Palindrome with k removes Next largest permutation Onsite: Make big island Cheese game Random pick (only return from largest) LCA ML Design: Design ads evaluation framework Behavioral: Asked about my research, why phd? why leave to industry?...
Meta Phone Screen MLE E5
Giving back to community Question 1: https://leetcode.com/problems/lowest-common-ancestor-of-a-binary-tree-iii/description/ First gave O(n) solution but E wanted me to optimize. Then gave O(1) solution Follow-up: "How can you prove that the O(1) solution would converge?" I fumbled...
Meta IC4 Phone Screen SWE-ML
Hello, I had my phone screen a few days ago. It was a success so I\'m preparing for the final round of interviews. Phone Screen 1. Regular LC easy problem. 2. https://leetcode.com/problems/word-break-ii/description/ This was a...
Pass / Fail - MLE 2 (E4) @ Meta
Hey guys, Phone screen (Oct 3rd week) tree traversal - similar to boundary of tree array traversal - similar to minimum subarray k sum Aced - move to onsite - got back in ~5...
META | Phone Screen | E5/E6 | London | MLE
Had the Phone screen with Meta Yesterday. The phone screen was for E5/E6, hence it is 1 hr . First 15 minutes was for behavioural questions and then I was...
Meta E5 interview
Software Engineer - ML So far I\'ve completed phone screen and technical onsite. Pending behavioral Phone Screen 1. https://leetcode.com/problems/subarray-sum-equals-k/ 2. https://leetcode.com/problems/palindrome-permutation/ Virtual Onsite 1. Coding Round 1 \t- Count number of...
Meta | E4 MLE | NYC | Offer
I want to give back to the community which was incredibly helpful to my interview preparation. Background: - Years of Experience: 0 (Recently completed a PhD with one internship at a FAANG...
Facebook | E4 | NYC | Spring 2021 [Offer]
Status: New grad, PhD CS Top 20 CS school Position: Research Scientist at Facebook Location: NYC Date: Spring 2021 Technical Phone Screen (1 hour) - Behavioural questions - Questions about my research experience -...
Location : London Post : Software Engineer, Machine Learning (MLE) YOE : 4 I had my phone screen with facebook for MLE recently. Question asked : Let\'s say we have database all the customer...
Facebook | Phone | Subarray Sum Equals K & Min Remove to Make Valid Parentheses
I had a technical phone screen on 4/15 for SWE-ML. 45 mins with two coding questions. Interviewer was nice, tried to help me when i got stuck. Personally haven\'t had...
Last week I had my facebook phone interview for Ph.D. intern(ML). The interviewer asked me the following question. You are given a dictionary of word and a sentence. Find all the...
[NDA] Facebook SWE Interview Experience (Menlo Park/ New York / Seattle)
Just received an offer from Facebook. So excited as I\'ve been preparing for almost half a year and finally! During this half year, Leetcoding has become my daily routine and...
What to Expect in the Meta Phone Screen Round
The Meta Machine Learning Engineer Phone Screen round has a specific calibration purpose distinct from other rounds in the loop. Across 22+ verified reports on LeakCode for this exact round type, the consistent expectations: clear scoping of the problem before diving into a solution, explicit reasoning about complexity, structured handling of edge cases, and the ability to discuss trade-offs between two reasonable approaches.
Reports tagged with the Phone Screen round at Meta show recurring patterns in difficulty and topic distribution. The Phone Screen round is typically 45-60 minutes; the interviewer is calibrated against a specific rubric. The discriminator between candidates who advance and candidates who do not is rarely the final correctness of the answer. It is the path: did you clarify, did you verbalize your approach, did you handle edge cases, and did you communicate throughout.
How To Prepare for This Specific Round
Filter the questions below to the most recent reports (past 6-12 months). Questions tagged for this exact round type from this exact company at this exact role level are the highest-signal data available. Older reports may reference questions that have since rotated out of the company's pool.
Practice 4-6 representative problems from this set under timed conditions. The goal is not memorization (companies rotate questions); the goal is to internalize the patterns the interviewer typically reaches for and the depth of follow-up to expect. Reports on LeakCode also tag the typical follow-up depth at this round type, which is the discriminating signal between hire and no-hire calibration.
Phone Screen Round Timing and Format
The Phone Screen round at Meta typically runs 45-60 minutes. Use the first 2-3 minutes to clarify requirements; you should never start coding or designing without verifying the input/output format, constraints, and edge cases out loud. Use the next 5-7 minutes to verbalize your approach before writing any code. The middle 20-30 minutes are implementation. Reserve the final 10 minutes for testing with concrete examples and discussing optimization or trade-offs.
Time budget discipline is one of the most reliable senior-vs-junior discriminators in this round. Strong candidates verbalize where they are in their budget out loud ("I've used about 20 minutes, I have 15 minutes left for testing and one optimization"). This signals engineering maturity to the interviewer and creates positive feedback they can capture in writing.
Common Failure Modes in This Round
Reports tagged "no hire" at Meta Machine Learning Engineer Phone Screen commonly cite: coding silently without verbalizing approach, jumping to implementation before clarifying requirements, missing edge cases (empty input, single element, very large input), producing working code that the candidate cannot refactor when asked, and failing to test their solution with concrete examples before declaring done.
The single most predictive failure mode in 2025-2026 reports: not asking clarifying questions. Interviewers at all FAANG companies are explicitly trained to weight this dimension. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's notes.
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