Quantitative Trading & Research - Quantitative Developer Systematic Trading - Associate

Job Description

The Quantitative Trading & Research (QTR) group is responsible for systematic trading across FX, Rates, Commodities, Credit, Equity and a wide range of markets.

Within QTR, AI Market Lab brings together quantitative research, modern artificial intelligence, market microstructure, and high-performance engineering to develop the next generation of electronic trading capabilities.

Our work spans signal research, pricing, market making, execution, portfolio construction, risk management, and the production systems that support them.

We are hiring globally across New York, London, Singapore or Hong Kong.

Job Summary

As an Associate or Vice President for the QTR team, you will build the research and production technology behind AI-driven systematic trading.

You will work at the boundary of quantitative research, low-latency engineering, and ML infrastructure, creating reliable platforms that shorten the path from raw market data and research prototypes to monitored, resilient production strategies.

This role is ideal for engineers who enjoy turning ambiguous research requirements into clean interfaces, fast systems, and reproducible workflows-without losing sight of trading realities like latency, determinism, and operational risk.

Job Responsibilities


* Design and build high-performance market-data, feature-computation, backtesting, simulation, model-serving, execution, and monitoring components for systematic trading.


* Develop reliable low-latency C++ services and APIs that integrate quantitative models with real-time market data, pricing, risk controls, and order-management systems.


* Build scalable data and research pipelines that support granular historical data, reproducible experiments, distributed computation, and rapid strategy iteration.


* Optimize critical paths for throughput, tail latency, memory efficiency, resilience, and deterministic behavior; use profiling and measurement to guide engineering decisions.


* Productionize machine-learning models, including training workflows, model versioning, real-time inference, deployment automation, observability, and rollback controls.


* Partner with researchers and traders to translate strategy requirements into robust software, improve research-to-production consistency, and support live systems.

Required Qualifications


* Bachelor's, Master's, or PhD in computer science, engineering, mathematics, or a related technical discipline (or equivalent professional experience).


* 2+ years of professional experience in software engineering, quantitative development, low-latency systems, or ML infrastructure.


* Strong modern C++ skills: data structures, concurrency, memory management, performance profiling, and production debugging.


* Proficiency in Python and experience building software for quantitative researchers or other data-intensive applications.


* Solid understanding of distributed systems, testing, software design, re...