Mistral AI coding interview

Round 3 of 5 · 2 questions reported

Length: 60 min
Format: Live coding in Python
They grade: Clean, efficient Python and clearly explained tradeoffs
AI use: Reportedly fine for boilerplate and lookups; the fundamentals must be your own
Heads-up: LeetCode medium or harder, often with a practical angle such as data pipelines or embeddings. A 2026 New York report: on CodeSignal, one problem in three parts (GPUs left per cluster per day, then the most a workload can take, then the same with at most K switches, a dynamic program); budget time for the last part.

Questions Mistral AI asks in this round 2

Nearest-center assignment without an N x K x D distance tensorCodingGiven N points and K centers in D dimensions, assign each point to its nearest center, as in the assignment step of k-means. The obvious broadcast builds an N x K x D array of…
Last asked Jul 2026
GPU clusters: capacity left per day and the best K-switch planCodingYou run a few GPU clusters with fixed daily capacities, for example 10, 20. Each day a list of usage records takes GPUs from clusters (a record names the day, the cluster and how…
Last asked Apr 2026