Nubank

Typical interview loop

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

1. 1

   Talent acquisition interview

   Focus: Background and culture fit

   A remote call with recruiters who explain the teams and openings while checking your background, technical skills, goals and culture fit.

2. 2

   Basic programming (live coding)

   Focus: Programming fundamentals

   A live coding session testing core programming skills.

3. 3

   ML architecture

   Focus: Productionising ML models

   You reason through how you would put machine learning models into production for a given scenario.

4. 4

   Advanced programming

   Focus: Applied engineering on business problems

   A harder technical round on applying your engineering knowledge to a business problem.

5. 5

   Leadership interview

   Focus: Values and seniority

   A final conversation with leaders to confirm values and seniority level, where they also explain the area's challenges and expectations.

Topics to prepare for Nubank

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

• GenAI system designSystem design
• Python for ML interviewsCoding
• Cost and latency engineering for LLM appsSystem design
• Calling LLM APIs in Python: async, streaming, retriesCoding
• 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
• Embeddings basics: word2vec, contrastive learning, what embeddings captureML fundamentals

How it weights your plan

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