Scale AI Machine Learning Interview Questions

These are the 5 Scale AI machine learning interview questions AceOffer has reconstructed from candidate reports, sorted by how often each was reported. LLM Theory Round: Transformers, Sampling, Fine-Tuning and RL leads at 5×. Every question shows when it was last reported; the catalog refreshes monthly.

Part of the full catalog of Scale AI interview questions, covering every round.

Key facts

•5 distinct machine learning questions indexed
•16 candidate reports across those questions
•Most reported: LLM Theory Round: Transformers, Sampling, Fine-Tuning and RL — 5× (last seen April 2026)
•Refreshed monthly · last updated October 2026

Which Scale AI rounds ask machine learning questions?

The Scale AI rounds below are where these questions come up. Counts are distinct questions, not times asked.

For ML roles: an LLM theory round from regularization and tokenization through fine-tuning and RL methods, NumPy implementations of top-p sampling and attention in Colab, debugging an LLM project after writing a data parser, and take-homes built on jailbreaking GPT-2: a 2025 intern take-home with a prompt-engineering question and a jailbreak algorithm to implement, and a 6-hour Colab OA that implements the attack from a named paper.4 questions

Most reported: LLM Theory Round: Transformers, Sampling, Fine-Tuning and RL — 5×

A project presentation of 30 to 45 minutes on your own work or a paper; interviewers may be generalists, so candidates advise making it metrics-driven and easy to follow outside your field.1 question

Most reported: Project Presentation Round — 4×

Which Scale AI machine learning questions get asked most?

Sorted by candidate-report frequency. Click any question for the full breakdown.

Question	Round	Reported	Last seen
LLM Theory Round: Transformers, Sampling, Fine-Tuning and RL A spoken LLM theory round, 60 minutes in one onsite report and 30 minutes as the first of two back-to-back phone-screen rounds…	MLE	5×	April 2026
Project Presentation Round Present one of your own projects, or a previous paper, to an interviewer. Reports give 30 minutes (an MLE loop, presenting a…	Tech Deep Dive	4×	August 2026
ML Debugging: Parse Conversation Data, Then Fix an LLM Project A 60-minute ML round in two parts, done in one session. First you write a simple parser for conversation data; then you…	MLE	3×	March 2026
ML Take-Home: Reproduce a GCG Jailbreak on GPT-2 Two reports describe an ML take-home built on GPT-2 jailbreaking. 2025 ML intern take-home (two questions). (1) Prompt engineering: given several keywords,…	MLE	2×	December 2025
ML Coding: Top-p Sampling and Multi-Head Attention in NumPy You implement four functions in three graded parts, in NumPy, not PyTorch, in a notebook that already defines softmax and comes with…	MLE	2×	March 2026

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FAQ

How many machine learning questions does Scale AI ask?▾

AceOffer has reconstructed 5 distinct Scale AI machine learning interview questions from 16 verified candidate reports, each with verbatim follow-ups and a last-reported date.

What is the most common Scale AI machine learning interview question?▾

LLM Theory Round: Transformers, Sampling, Fine-Tuning and RL — reported 5 times, last seen April 2026.

How fresh is AceOffer's Scale AI machine learning question data?▾

The catalog is refreshed monthly from new candidate reports, and every question shows when it was last reported.

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