Microsoft Azure AI platform team Interview Experience
Summary
I recently interviewed for the Microsoft Azure AI platform team. The interview consisted of two rounds: a Data Structures and Algorithms question involving grid optimization and a System Design challenge to build an AI training SaaS on Azure.
Full Experience
My interview experience for the Microsoft Azure AI platform team involved two distinct rounds. The first round, a DSA interview, presented a problem focused on optimizing office placements within a grid, aiming to minimize the maximum distance from any lot to the nearest office. Given the specific constraints, I discussed a brute force approach combined with multi-source BFS to solve it.
The second round was a comprehensive system design challenge. I was tasked with designing a software-as-a-service platform capable of training customer codebases and data on Azure cloud, leveraging Nvidia GPUs. Key considerations for this design included handling a large scale of 25,000 GPUs and 100,000 customers, managing billing, ensuring data segregation, and supporting the entire lifecycle of training jobs from submission to result storage, monitoring, and error handling.
Interview Questions (2)
Given a grid of size w x h, place n office buildings such that the maximum distance from any lot to the nearest office is minimized. Movement is 4-directional (no diagonals).
Design a Software as a Service (SaaS) platform to enable customers to train their codebases and data directories on Azure cloud, utilizing Nvidia GPUs. The system must support a significant scale, handling 25,000 GPUs and 100,000 customers, with robust mechanisms for billing and data segregation.
Users should be able to submit training jobs, specifying their custom code, data, and container images, along with their GPU requirements. The platform needs to manage the entire lifecycle of these training jobs, including resource provisioning, execution, real-time monitoring, error handling, secure storage of results, and comprehensive billing for services consumed.