Klarna

Typical interview loop

How Klarna usually runs it for applied AI and LLM engineer roles.

1. 1

   Recruiter screen

   Focus: Background and motivation

   A 30-minute call on your ML background and why you want to work on Klarna's AI and payments problems.

2. 2

   Logic / aptitude test

   Focus: Abstract reasoning

   A short, timed, video-proctored abstract-reasoning test that candidates describe as a hard filter.

3. 3

   Technical assessment

   Focus: ML fundamentals, implementation

   A take-home ML project or coding assessment of a few hours covering data processing and model implementation.

4. 4

   Technical interviews

   Focus: ML design, coding, MLOps

   Several rounds mixing ML system design, Python/SQL coding and an ML concepts deep dive that includes deployment and MLOps.

5. 5

   Behavioral / leadership round

   Focus: Leadership principles

   A conversation about past work and how you handle disagreements, scored against Klarna's leadership principles.

Topics to prepare for Klarna

The topics its loop weighs most, each with what interviewers check and what to study.

• GenAI system designSystem design
• Behavioral interviews: STAR stories for AI engineersBehavioral
• Embeddings basics: word2vec, contrastive learning, what embeddings captureML fundamentals
• Cost and latency engineering for LLM appsSystem design
• The project deep-dive roundBehavioral
• RAG vs fine-tuning vs prompting: choosing the approachSystem design
• Design an AI customer-support agentSystem design
• Design enterprise document search / a knowledge assistantSystem design

How it weights your plan

Selecting Klarna when you build a plan multiplies each topic’s priority score: