AI-Driven Quant Developer for Low-Latency Markets

JPMorganChase; Hong Kong; On-site; HKD 1,200,000 - 1,800,000; Full time

Job summary

J.P. Morgan is seeking a quantitative developer to build the research and production technology behind AI-driven systematic trading in Hong Kong.

You will work at the boundary of quantitative research, low-latency engineering, and ML infrastructure to create reliable platforms that shorten the path from data and prototypes to monitored production strategies. This role emphasizes turning ambiguous research requirements into clean interfaces, fast systems, and reproducible workflows with attention

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, reliability, and operating production services end-to-end.
• Evidence of owning performance-critical systems from design → deployment → monitoring → incident resolution.

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.

Skills

C++

Python

Distributed systems

Performance profiling

Production debugging

Real-time systems

ML infrastructure

Education

Bachelor's/Master's/PhD in CS/Engineering/Math

Tools

PyTorch

JAX

CUDA

GPU clusters

Ray

Kafka

Kubernetes

Spark

Job description

J.P. Morgan is seeking a quantitative developer to build the research and production technology behind AI-driven systematic trading in Hong Kong.

You will work at the boundary of quantitative research, low-latency engineering, and ML infrastructure to create reliable platforms that shorten the path from data and prototypes to monitored production strategies. This role emphasizes turning ambiguous research requirements into clean interfaces, fast systems, and reproducible workflows with attention