2020–2026 Microsoft CoreAI and AI/ML Intern OA / Interviews: 118 Experiences (Part 7 :)

This part preserves 17 Microsoft AI/ML internship reports from 2020–2021.

Coverage: 2020–2021 · candidate reports 075–091 · 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.

2021 reports (continued)

075: Data & Applied Scientist Intern — phone or technical screen

Report date: 2021-09-28 · Role: Data & Applied Scientist Intern · Stage: Phone / technical screen

Microsoft Data & Applied Scientist Intern first-round report. The 30-minute screen contained resume, collaboration, and impact questions followed by basic statistics and ML-concept discussion, with no coding exercise.

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

Other reported topics or limits: Behavioral and Basic ML Concept Screen.

076: Data/Applied Scientist Intern — final interview loop

Report date: 2021-09-15 · Role: Data/Applied Scientist Intern · Stage: Final loop / onsite

Detailed Microsoft Data/Applied Scientist internship report for an NLP group.

1. Maximum Sum Increasing Subsequence. Given an array, consider all increasing subsequences. Return the maximum possible subsequence sum.

Other reported topics or limits: Array Median with Restricted Operations; Undisclosed NLP Case Study; Candidate-Specific Deep Learning Project Follow-Ups.

077: Data Scientist PhD Intern — final interview loop

Report date: 2021-03-20 · Role: Data Scientist PhD Intern · Stage: Final loop / onsite

Detailed Microsoft Data Scientist PhD internship offer report for a Bing Maps placement.

1. Maximum Subarray Sum. Given an array, find the maximum sum of a contiguous subarray.
2. Find All Unique Two-Sum Pairs. Solve a Two Sum variant. Return every distinct pair.
3. Find All Primes Less Than N. Given n, return all prime numbers less than n.

Other reported topics or limits: Compare Two Companies' Similar Apps; One Forgotten Easy Coding Task; Behavioral, Project, ML, Data-Structure, and SQL Knowledge Discussion.

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

Report date: 2021-03-01 · Role: Applied/Data Scientist PhD Intern · Stage: Final loop / onsite

Detailed Microsoft Applied/Data Scientist PhD internship onsite report.

1. Compute Variance in O(n) Time. Given numerical observations, compute their variance. The required time complexity is O(n).
2. Diagnose Bias in Product Feedback Data. Given a dataset, determine whether it is biased. For low feedback scores, distinguish product-caused dissatisfaction from other causes.
3. Formulate and Solve Cloud Resource Allocation. Formulate a cloud-computing resource-allocation problem. Explain how to solve the resulting formulation.

Other reported topics or limits: Explain P-Values and Confidence Intervals.

079: Data Scientist Intern — phone or technical screen

Report date: 2021-02-25 · Role: Data Scientist Intern · Stage: Phone / technical screen · Interview date: 2021-02-25

Detailed Microsoft Data Scientist internship technical screen.

1. Label a Million-Row Dataset from a Smaller Labeled Set. Dataset A contains approximately 100,000 labeled rows. Dataset B contains millions of rows and needs labels. Propose an effective labeling solution.
2. Even-Valued Elements at Even Indices. Given a list, return every element whose index is even and whose value is also even.

Other reported topics or limits: Resume Project and Job-Description Match Discussion.

080: Microsoft Research NLP Intern — final interview loop

Report date: 2021-02-19 · Role: Microsoft Research NLP Intern · Stage: Final loop / onsite

Microsoft Research NLP internship video interview. Roughly twenty minutes focused on the candidate's research, followed by about ten minutes discussing an algorithm described only as similar to 3Sum and its complexity. The exact variant was not shared.

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

Other reported topics or limits: Unspecified 3Sum-Like Algorithm; Candidate-Specific Research Deep Dive.

081: Data Science PhD Intern — phone or technical screen

Report date: 2021-02-16 · Role: Data Science PhD Intern · Stage: Phone / technical screen · Interview date: 2021-02-16

Detailed Microsoft Data Science PhD internship background screen. The interviewer asked about ML interests, publications, research collaboration, proudest work, programming language, resume items, collaboration difficulty, explaining deep learning to a child, and a preferred Microsoft product. No reusable standalone artifact was requested.

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

Other reported topics or limits: ML Interests, Publications, Collaboration, and Product Screen.

082: Applied & Data Scientist PhD Intern — final interview loop

Report date: 2021-02-04 · Role: Applied & Data Scientist PhD Intern · Stage: Final loop / onsite · Interview date: 2021-02-04

Microsoft Applied & Data Scientist PhD internship onsite report.

1. Compute Variance. Write code to compute variance.
2. Diagnose Bias in a Dataset. Explain how to determine whether a dataset is biased.

Other reported topics or limits: Explain P-Values.

2020 reports

083: Microsoft Research Intern — phone or technical screen

Report date: 2020-12-18 · Role: Microsoft Research Intern · Stage: Phone / technical screen · Interview date: 2020-12-18

Microsoft Research internship report from a fourth-year PhD. Two one-hour interviews were entirely research-focused: the candidate presented recent work and answered detailed follow-ups about it. There was no coding or general technical-question round. The candidate later reported receiving an offer on December 29.

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

Other reported topics or limits: Present Recent Research and Answer Detail Questions.

084: Data & Applied Science PhD Intern — phone or technical screen

Report date: 2020-12-16 · Role: Data & Applied Science PhD Intern · Stage: Phone / technical screen · Interview date: 2020-12-16

Detailed Microsoft Data & Applied Science PhD internship first-round screen for the 2021 internship cycle. Questions covered ML interests, projects, publications, collaboration, programming languages, explaining deep learning to a child, Microsoft product improvement, motivation, and team preference. No reusable standalone artifact was requested.

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

Other reported topics or limits: ML Interests, Projects, Publications, Collaboration, and Product Screen.

085: Data Scientist Intern — phone or technical screen

Report date: 2020-12-14 · Role: Data Scientist Intern · Stage: Phone / technical screen · Interview date: 2020-12-08

Detailed Microsoft Data Scientist master's internship first round. The NLP-team interviewer spent about twenty-five minutes on one resume project, communication difficulty, model validation, and explaining p-values to a non-statistician. The author explicitly reports no coding and no case study.

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

Other reported topics or limits: Resume Project, Communication, Validation, and P-Value Screen.

086: Applied & Data Scientist Intern — final interview loop

Report date: 2020-12-09 · Role: Applied & Data Scientist Intern · Stage: Final loop / onsite · Interview date: 2020-12-09

Detailed Microsoft Applied & Data Scientist master's internship onsite.

1. Convert a Binary Search Tree to a Doubly Linked List. Convert a binary search tree into a doubly linked list.
2. Count Trailing Zeros in N Factorial. Given n, count the number of trailing zeros in n factorial.
3. Bold a Target Substring in an HTML Article. The input is an HTML article and start and end indices for a target string. Modify the HTML so the target string appears bold.
4. Design a Highway Toll Booth System. Design a highway toll booth on a whiteboard. Identify interacting components. Write high-level pseudocode for classes and functions.

Other reported topics or limits: XGBoost and Recommendation/NLP Improvement Discussions.

087: Data Scientist Intern — phone or technical screen

Report date: 2020-12-06 · Role: Data Scientist Intern · Stage: Phone / technical screen · Interview date: 2020-12-04

Microsoft Data Scientist internship first-round update. The author characterizes the round as behavioral questions plus simple algorithms, but only discloses motivation and candidate-specific project/challenge prompts; no algorithm identity or task details are given.

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

Other reported topics or limits: Motivation, Project Challenge, and Data-Science Problem Questions; Undisclosed Simple Algorithm Questions.

088: Data & Applied Science Intern — phone or technical screen

Report date: 2020-12-05 · Role: Data & Applied Science Intern · Stage: Phone / technical screen · Interview date: 2020-12-04

Detailed Microsoft Data & Applied Science master's internship first round. At least half of the interview covered motivation and candidate-specific project challenges, followed by one easy LeetCode-style Python task that the author solved using enumerate but never disclosed. A later update confirms a virtual-onsite invitation without adding questions.

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

Other reported topics or limits: Motivation, Project Challenge, and General Data-Science Problem Screen; Undisclosed Easy LeetCode-Style Python Task Using Enumerate.

089: Applied Data and Science PhD Intern — phone or technical screen

Report date: 2020-12-02 · Role: Applied Data and Science PhD Intern · Stage: Phone / technical screen

Detailed Microsoft Applied Data and Science PhD internship first-round interview for the 2021 cycle.

1. Detect Fake News from One Day of Tweets. Given one day's tweets, design an approach to identify fake news. The interview discussion may consider signals such as positive versus negative comments.
2. Output Consecutive Numbers in an Array. Given an array, output its consecutive numbers.

Other reported topics or limits: Text-Mining Project and Difficult Teammate Discussion.

090: Data Scientist PhD Intern — phone or technical screen

Report date: 2020-11-18 · Role: Data Scientist PhD Intern · Stage: Phone / technical screen

Detailed Microsoft Data Scientist PhD internship screen.

1. First Missing Positive. Given an integer array, return the smallest missing positive integer. The task matches LeetCode 41.

Other reported topics or limits: Area Interest and Child-Friendly Internet Explanation.

091: Data & Applied Science PhD Intern — phone or technical screen

Report date: 2020-11-16 · Role: Data & Applied Science PhD Intern · Stage: Phone / technical screen

Detailed Microsoft Data & Applied Science PhD internship first-round screen. The interview covered self-introduction, NLP experience, a challenging project and model evaluation, explaining deep learning to a child, motivation, and Microsoft product improvement. Later posts only discuss delayed scheduling and add no interview question.

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

Other reported topics or limits: NLP, Project Evaluation, Motivation, and Product Screen.

Part 8 continues with the next candidate reports.