2020–2026 Microsoft CoreAI and AI/ML Intern OA / Interviews: 122 Experiences (Part 3 :)

This part preserves 15 Microsoft AI/ML internship reports from 2022–2024.

Coverage: 2022–2024 · candidate reports 020–034 · phone screens and final loops

Series note: Part 1 focuses on the CoreAI / AI-ML Software Engineering Intern loop. This part preserves other Microsoft AI/ML internship reports without treating them as CoreAI SWE evidence.

2024 reports (continued)

020: Research Intern — final interview loop

Report date: 2024-03-06 · Role: Research Intern · Stage: Final loop / onsite · Interview date: 2024-03-06

Detailed Microsoft product-oriented research-team summer-intern offer report. The first round aligned research interests and projects; the second round with an applied scientist included an ML-design question for the summer project; the third covered research experience and behavioral questions, with no coding test.

1. No standalone technical prompt was preserved. This entry is retained for its process, timing, role, or interview-format evidence.

Other reported topics or source limits: Design the ML Approach for an Unnamed Summer Project; Research Alignment, Technology Familiarity, and Behavioral Questions.

021: Mixed Reality Research Scientist Intern — phone or technical screen

Report date: 2024-01-16 · Role: Mixed Reality Research Scientist Intern · Stage: Phone / technical screen

Microsoft Mixed Reality Research Scientist Intern coding report with one concrete in-place word-order reversal task.

1. Reverse Word Order In Place. Reverse the order of words in a string. The characters within each word remain unchanged. The interviewer required an in-place solution.

2023 reports

022: Data Scientist Intern — final interview loop

Report date: 2023-10-21 · Role: Data Scientist Intern · Stage: Final loop / onsite · Interview date: 2023-10-01

Detailed Microsoft Data Scientist internship offer report.

1. Unnamed SQL Medium Whiteboard Task. The first virtual-onsite round included one SQL Medium problem written on a whiteboard. The report did not preserve a reconstructable task contract.

Other reported topics or source limits: Two Contextual NLP/ML Cases; Recommendation Data, Metrics, and Customer-Segmentation Case; Experimentation, NLP Concepts, and Behavioral Questions.

023: Data Scientist Intern — final interview loop

Report date: 2023-10-14 · Role: Data Scientist Intern · Stage: Final loop / onsite · Interview date: 2023-10-04

Microsoft Data Scientist Intern final-round report with three rounds.

1. Search in Rotated Sorted Array. The original author identifies the first-round coding task as LeetCode 33. The author completed it quickly with one less-than-or-equal versus less-than bug.
2. Binary Tree Right Side View. The original author identifies the third-round coding task as LeetCode 199. The first solution used DFS and the interviewer requested a BFS rewrite.

Other reported topics or source limits: Time-Series Anomaly Detection Case; Bing Ads DS Interview Loop Shared by a Commenter.

024: Applied Scientist Intern — final interview loop

Report date: 2023-10-13 · Role: Applied Scientist Intern · Stage: Final loop / onsite · Interview date: 2023-10-12

Microsoft Applied Scientist Intern final-round report.

1. Unspecified Applied Scientist Coding Question. The second final-round interview was a coding round. The report did not preserve a reconstructable task contract.

Other reported topics or source limits: Unspecified ML Design Round; Unspecified ML Theory Round.

025: Microsoft Research Intern — final interview loop

Report date: 2023-03-09 · Role: Microsoft Research Intern · Stage: Final loop / onsite · Interview date: 2023-02-08

Microsoft Research internship pass report.

1. Unnamed Simple Coding Question. A senior interviewer asked one simple coding question during the follow-up round. The report did not preserve a reconstructable task contract.

Other reported topics or source limits: Candidate Research Talk and Proposal Discussion.

026: Office of Applied Research Intern — phone or technical screen

Report date: 2023-02-14 · Role: Office of Applied Research Intern · Stage: Phone / technical screen

Microsoft Office of Applied Research internship pass report. Three research scientists conducted two rounds about the candidate's research and project ideas; the post gives no coding or reusable design prompt.

1. No standalone technical prompt was preserved. This entry is retained for its process, timing, role, or interview-format evidence.

Other reported topics or source limits: Discuss Research and Project Ideas.

027: Microsoft Research Computational Biology Intern — final interview loop

Report date: 2023-02-10 · Role: Microsoft Research Computational Biology Intern · Stage: Final loop / onsite

Microsoft Research Health Futures computational-biology summer-intern report. The process moved from a principal-researcher screen to two senior-researcher interviews and a director conversation, centered on research projects, big-picture insight, ML, and generative-model knowledge.

1. No standalone technical prompt was preserved. This entry is retained for its process, timing, role, or interview-format evidence.

Other reported topics or source limits: Computational-Biology, ML, and Generative-Model Research Discussion.

2022 reports

028: Data Scientist / Applied Scientist PhD Intern — final interview loop

Report date: 2022-12-24 · Role: Data Scientist / Applied Scientist PhD Intern · Stage: Final loop / onsite

Detailed Microsoft Device-team Data Scientist/Applied Scientist PhD internship loop.

1. Design a System to Detect and Correct User String Typos. Given a user-entered string, determine whether the user typed it incorrectly. If the string is wrong, produce or select the corrected string.

Other reported topics or source limits: Unspecified Third-Round Case Study; Semi-Supervised Learning Case Study; Behavioral, Model-Detail, and DP-to-a-Child Discussion.

029: Research Intern — final interview loop

Report date: 2022-12-19 · Role: Research Intern · Stage: Final loop / onsite · Interview date: 2022-02-18

Concise Microsoft Research internship offer timeline. Two researcher conversations asked about ownership of prior implementation and the candidate's ideas for potential methods in an unnamed research area.

1. No standalone technical prompt was preserved. This entry is retained for its process, timing, role, or interview-format evidence.

Other reported topics or source limits: Propose a Potential Method for an Unnamed Research Problem; Implementation Ownership Discussion.

030: Applied Sciences Group Research Intern — final interview loop

Report date: 2022-12-01 · Role: Applied Sciences Group Research Intern · Stage: Final loop / onsite · Interview date: 2022-12-01

Microsoft Applied Sciences Group research-intern report from a third-year PhD in an AI-adjacent field.

1. Unspecified Recursive Backtracking Combination Task. The coding task required recursive backtracking. The original author recalls that it was roughly about finding all combinations. The report did not preserve a reconstructable task contract.

Other reported topics or source limits: Compute a Bayesian Posterior from Error Rates; Research Talk and ML Breadth/Depth Discussion.

031: Data Scientist / Data & Applied Scientist Intern — final interview loop

Report date: 2022-11-29 · Role: Data Scientist / Data & Applied Scientist Intern · Stage: Final loop / onsite

Microsoft DSA internship final-round report.

1. Unnamed LeetCode Easy Codility Task. The first round used Codility for one LeetCode Easy-level algorithm problem. The report did not preserve a reconstructable task contract.
2. Unnamed SQL Task. The second final-round interviewer asked the candidate to write one SQL solution. The report did not preserve a reconstructable task contract.

Other reported topics or source limits: Unspecified Data-Science Case; Resume ML, High-Level DS, and Preference Discussion.

032: Data & Applied Sciences Intern — phone or technical screen

Report date: 2022-11-04 · Role: Data & Applied Sciences Intern · Stage: Phone / technical screen

Microsoft Data & Applied Sciences internship first-round phone screen. The conversation covered proudest project, teamwork difficulty, explaining ML, motivation for Microsoft and data science, coding skills, qualification, and ML algorithms used in prior projects.

1. No standalone technical prompt was preserved. This entry is retained for its process, timing, role, or interview-format evidence.

Other reported topics or source limits: Behavioral, ML Explanation, and Project-Algorithm Screen.

033: Data Scientist Intern — final interview loop

Report date: 2022-10-31 · Role: Data Scientist Intern · Stage: Final loop / onsite · Interview date: 2022-10-31

Detailed Microsoft Bing Search Data Scientist internship offer loop.

1. Find the Nth Percentile, Including a Large Unsortable Input. Given a list of integers, find the Nth percentile. Follow-up: the list is very large and cannot be sorted in full.
2. Estimate Pi Using Uniform[0,1] Samples. Use samples from a Uniform[0,1] source to estimate the value of pi.
3. Compute a Median and Maintain It as Numbers Arrive. Given a number list, compute its median. Follow-up: maintain the median while numbers are added one at a time.
4. Generate a Uniform Bounded Integer from Bernoulli(p). Given access to Bernoulli(p), generate randint(a,b). The source gives randint(1,10) as an example.
5. Implement an LRU Cache. Implement an LRU Cache.
6. Design Website Classification with Crowdsourced Label Quality Controls. Design a classifier for websites. Discuss feature choices such as domain and page content. Labels come from crowdsourcing; address label quality and class imbalance. Estimate crowd quality by injecting examples with known labels and measuring correctness.

Other reported topics or source limits: ML Fundamentals and Behavioral Questions.

034: Data Scientist and Applied Scientist Intern — final interview loop

Report date: 2022-10-11 · Role: Data Scientist and Applied Scientist Intern · Stage: Final loop / onsite · Interview date: 2022-10-10

Detailed Microsoft Data Scientist and Applied Scientist internship offer report.

1. Wrap Text to 80 Characters Without Splitting Words. Given a very long text string, format it for printing with at most 80 characters per line. A line ending must not split a word. No output line may begin with a space. The interviewer asked for time and space complexity.
2. Design User Targeting for Account, Subscription, and Data-Sharing Conversion. Design how to identify users likely to create a Microsoft account. Design how to identify existing account holders likely to purchase a subscription. Design how to persuade or identify users likely to consent to sharing data. The discussion considered device count, OneDrive capacity usage, and engagement frequency as candidate features. A follow-up asked how to use data to convince a product manager that the selected users are the right target.
3. Represent a Directed Entity Network and Predict New Links. Entities form directed links such as A to B, B to C, C to D and A, and D to A and C. Choose a data structure to represent the network. Extend the representation to weighted edges and explain how to assign weights. When a new node arrives, predict which existing nodes it will connect to. Discuss whether outliers should be removed. The candidate proposed node embeddings and similarity for link prediction.

Other reported topics or source limits: Python Scope, Deep-Learning Explanation, and Behavioral Questions.

Part 4 continues with the next candidate reports.