Hudson River Trading
Research Engineer
$200K–$300K
London, United Kingdom +7 · Full-time · Posted Feb 2, 2026
- Location
- London, United Kingdom
New York, NY, United States
Austin, TX, United States
Boulder, Colorado, United States
Chicago, Illinois, United States
London, United Kingdom
New York, NY, United States
Seattle, Washington, United States - Experience
- No specific number of years stated; previous experience at a top-tier finance or technology company is required.
- Education
- Completed a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
About the job
Develops and maintains software and research systems that support quantitative trading teams, improve research workflows, and help deploy and monitor trading strategies.
What you'll do
- Design, develop, maintain, and optimize robust, performant, scalable software systems; debug distributed-system issues.
- Improve the mechanics and usability of Algo Developer research workflows, including tools for expressing and backtesting predictive signals.
- Support shared trading platforms and systems for simulation, live trading, and deployment across teams.
What they ask for
- Completed a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
- Previous experience at a top-tier finance or technology company with an excellent track record of rapid advancement and superlative reviews.
- Strong understanding of data structures, algorithms, and design principles; proficiency in Python or C++ will be assessed.
- Kindness and empathy; excellent written and verbal communication skills.
Nice to have
- Experience supporting internal users; hands-on experience with quant research and/or ML/Deep Learning platforms is a bonus.
- Experience with Python numerical, ML, and data-oriented libraries such as pandas, scikit, and pytorch; management experience is a bonus.
Pay
200,000 to 300,000 USD per year (base salary)
Tools
Python, C++, pandas, scikit, pytorch
AI focus
Aiding the development and deployment of very large deep learning models for live trading, and supporting ML/Deep Learning platforms.
Model-written summary · the original posting is authoritative