Hudson River Trading
Quant trading firm running deep learning on market data via HRT AI Labs
Interview in a few hours? A quick sprint for Hudson River Trading
AI in interviews
HRT's job postings ban AI tools in interviews and assessments unless you're told otherwise. They say HRT checks that answers are your own, and that detected use can end the interview, disqualify you or void an offer.
Typical interview loop
How Hudson River Trading usually runs it for applied AI and LLM engineer roles.
- Focus: Resume and role fit
Application review
You apply to one posting only and should expect up to about two weeks for HRT to review it.
- Focus: Algorithms under time pressure
Coding test
A timed online coding test whose length and topics depend on the role, taken in C++ or Python.
- Focus: Live coding, probability
Technical phone screens
One or two live screens. Engineers code live, while algorithm developers usually get one statistics screen and one coding screen.
- Focus: Coding depth, systems, quant reasoning
Onsite final
A multi-round final of one-on-one interviews mixing deeper coding and debugging, design or performance discussion, probability, and data analysis in Python for algo roles.
Topics to prepare for Hudson River Trading
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
- GenAI system designSystem design
- Embeddings basics: word2vec, contrastive learning, what embeddings captureML fundamentals
- 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 Hudson River Trading when you build a plan multiplies each topic’s priority score:
Official prep and resources
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