Experienced Research Engineer

Hudson River Trading (HRT) is a quantitative trading firm at the forefront of technological innovation. We build and deploy cutting‑edge systems within one of the world’s most advanced computing environments to power our global trading operations. Our non‑siloed, collaborative coding environment empowers talented engineers to make significant contributions and see their impact daily. At HRT, you’ll be challenged to solve the most complex problems in trading alongside many of the brightest minds in the field. We are seeking highly motivated and skilled Research Engineers who will work very closely with our Algo Developer (Quant Research) trading teams. These roles require exceptional programming fundamentals, a strong user focus, and the ability to thrive in a fast‑paced environment with constantly evolving requirements. Multitasking and context switching are inherent aspects of this role, through which you will gain insight into the ideation and execution of some of the world’s most sophisticated trading strategies.

Research Engineers at HRT work on a wide variety of projects. Examples include:

• Designing highly customized quantitative systems that enable Algo Developers to easily express and backtest new predictive signals.
• Building world‑class research tooling to speed up Algo Developers’ research iteration.
• Aiding the development and deployment of very large deep learning models for HRT’s live trading.
• Improving HRT’s monetization systems which turn our predictions into profitable trades.
• Evaluating sim vs. live differences to improve the fidelity of our simulations.
• Building systems to monitor and manage live trading.
• Specializing in specific time horizons, from high frequency trading to mid‑to‑low frequency hedge fund‑style strategies.
• Working across a very wide variety of asset classes (from equities to fixed income to options) and regions (from North America to Asia Pacific).

Responsibilities:

• Design, develop, and maintain robust, performant, and scalable software systems.
• Optimize existing codebases for performance, reliability, and efficiency.
• Debug complex issues across distributed systems in a time‑sensitive environment.
• Optimize both the mechanics and ergonomics of Algo Developer research workflows; this requires developing a deep intuition for research methodologies.
• Balance the short term goals of individual trading teams with the longer term goals of HRT’s generalized trading platforms across trading teams.
• Share technology and ideas with REs on different trading teams.

Qualifications:

• 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.
• Experience with supporting internal users is preferred; bonus if you have real hands‑on experience with quant research and/or ML/Deep Learning platforms.
• Experience with Python numerical, ML and data‑oriented libraries is a big plus (e.g. pandas, scikit, pytorch, etc.).
• Candidates should be prepared for technical interviews in either Python or C++.
• Proficiency in one of these languages will be assessed during the interview process.
• Kindness and empathy is a real requirement.
• Strong understanding of data structures, algorithms, and design principles.
• Excellent communication skills, both written and verbal.
• The ability to thoughtfully, methodically, and reliably deploy new software and features is a critical skill.
• If you have management experience, that’s always a bonus – but even so, expect to code!

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job‑related knowledge, skills, and experience. This role will also be eligible for discretionary performance‑based bonuses and a competitive benefits package. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.