Citadel
Hedge fund whose quant researchers apply ML to markets data at scale
Interview in a few hours? A quick sprint for Citadel
AI in interviews
No public policy found. Assume no AI assistance in live rounds unless your recruiter says otherwise.
Typical interview loop
How Citadel usually runs it for applied AI and LLM engineer roles.
- Focus: Algorithms under time pressure
Online assessment (software engineers)
Software engineering candidates take a timed HackerRank-style algorithms test; quant researchers usually skip this and go straight to live interviews.
- Focus: Coding, DSA, research ability
First-round video interview
A 45-60 minute remote interview on CoderPad mixing live coding, data structures and research-style problem-solving with questions about your background.
- Focus: Stats, ML, coding, research depth
Onsite technical interviews
Several back-to-back hour-long interviews with future teammates covering coding, statistics and ML, and a deep dive into your past research.
- Focus: Research style, team fit
Senior leadership interviews
Conversations with senior managers or a team lead about how you do research, how you collaborate and which team you fit.
Topics to prepare for Citadel
The topics its loop weighs most, each with what interviewers check and what to study.
- Python for ML interviewsCoding
- Calling LLM APIs in Python: async, streaming, retriesCoding
- Embeddings basics: word2vec, contrastive learning, what embeddings captureML fundamentals
- GenAI system designSystem design
- Cost and latency engineering for LLM appsSystem design
- 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 Citadel when you build a plan multiplies each topic’s priority score:
Official prep and resources
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