Associate Quantitative Trading Systems Engineer

JPMorgan Chase & Co.; Singapore; On-site; SGD 120,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. in Singapore seeks a quantitative developer to 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

Qualifications

• Bachelor’s degree in CS, engineering, mathematics, or a related technical field.
• 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++ development

Python

Low-latency systems

ML infrastructure

Quantitative development

Distributed systems

Performance profiling

Production debugging

Hardware-aware optimization

Education

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

Tools

PyTorch

JAX

CUDA

GPU clusters

Ray

Kafka

Kubernetes

Spark

Job description

JPMorgan Chase & Co. in Singapore seeks a quantitative developer to 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