# Devinterview-io/llms-interview-questions

🟣 LLMs interview questions and answers to help you prepare for your next machine learning and data science interview in 2026.

Repository: https://github.com/Devinterview-io/llms-interview-questions
Canonical: https://ross.abutalabs.com/products/llms-interview-questions
License Family: other
Topics: ai-interview-questions, coding-interview-questions, coding-interviews, data-science, data-science-interview, data-science-interview-questions, data-scientist-interview, interview-practice, interview-preparation, llms, machine-learning, machine-learning-and-data-science, machine-learning-interview, machine-learning-interview-questions, software-engineer-interview, technical-interview-questions, llms-interview-questions, llms-questions, llms-tech-interview
Last push: 2026-02-17T03:40:23+00:00

## Health v2 (maintenance only)
Score: 57/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 68, release rhythm 35, longevity 69
- inputs: {"age_days": 968, "days_push": 197, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1050, forks 121 (observed 2026-08-28T04:03:22.955879+00:00)

## What it is
A curated collection of 63 large language model interview questions with detailed answers, hosted on GitHub and Devinterview.io. It covers LLM fundamentals like Transformer architecture, tokenization, and attention mechanisms to help candidates prepare for machine learning and data science interviews.

## Use cases
- prepare for an llm interview
- study machine learning interview questions
- review transformer architecture concepts before an interview
- practice data science interview questions about large language models
- find answers to common llm technical questions
- brush up on llm knowledge for a software engineer interview

## When to choose
- you are preparing for a machine learning, data science, or software engineering interview involving LLMs
- you want a concise, question-driven review of LLM fundamentals
- you need free, curated interview prep material

## When to avoid
- you need hands-on code or a runnable library rather than study material
- you want comprehensive academic coverage of LLM theory
- you need up-to-date documentation for a specific LLM framework

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools
- domain: large-language-models, machine-learning, data-science, tutorials, education
- platform: -
- tags: interview-questions, interview-preparation, llms, study-guide, cheatsheet, web-server

## Member repositories
- Devinterview-io/llms-interview-questions (main) score 57

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:22.955879+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:00:15.100672+00:00, confidence not recorded.
  - readme: https://github.com/Devinterview-io/llms-interview-questions (fetched 2026-08-28T04:03:22.955879+00:00, sha b6db040e5e99)
- Data as of 2026-08-30T08:39:29.467469+00:00.