Quant jobs / Hudson River Trading

Research Engineer

A software engineer embedded with quant research teams who builds the tooling they use to backtest and deploy signals. It sits between research and the firm's shared trading platform.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Build and improve systems for expressing and backtesting predictive signals
Speed up researchers' iteration loops with better tooling
Help deploy large deep learning models into live trading
Investigate gaps between simulated and live results
Build monitoring for live trading systems

What they ask for

Required

Bachelor's or Master's in CS or engineering
Python or C++ proficiency
Data structures and algorithms
Reliable software deployment
Clear communication
Experience supporting internal users

Preferred

pandas, scikit-learn, PyTorch
Quant research or ML platform experience

Education: Bachelor's or Master's in computer science, engineering or a related technical field.
Experience: Prior experience at a strong finance or technology firm
Languages and tools: Python
C++
Markets: equities, fixed-income, options, multi-asset

How to prepare

Build a small backtesting framework with a clean API and tests
Practise algorithm and data structure problems in Python or C++
Learn how simulation differs from live trading (slippage, latency, fills)
Get comfortable with pandas and PyTorch workflows

What to study

The HFT Quant Developer roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on Hudson River Trading’s site before applying: requirements, location and pay can change after we check them.

View the posting on Hudson River Trading’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Hudson River Trading and doesn’t handle applications.