AI-Driven Quant Developer (Associate) | Low-Latency

JPMORGAN CHASE BANK, N.A.; Singapore; On-site; SGD 150,000 - 210,000; Full time

Job summary

JPMorgan Chase Bank, N.A. in Singapore seeks a quantitative developer to build the research and production technology behind AI-driven systematic trading. Work spans low-latency C++ services, ML infrastructure, and production pipelines for data, pricing, risk controls, and execution.

You will collaborate with researchers and traders to turn strategy requirements into robust software while maintaining latency, determinism, and operational risk considerations.

Qualifications

• 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

Experience in software engineering or/

C++ mastery

Python proficiency

Distributed systems understanding

Ownership of performance-critical UIs

Education

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

Tools

PyTorch

JAX

CUDA

GPU clusters

Ray

Kafka

Kubernetes

Spark

Job description

JPMorgan Chase Bank, N.A. in Singapore seeks a quantitative developer to build the research and production technology behind AI-driven systematic trading. Work spans low-latency C++ services, ML infrastructure, and production pipelines for data, pricing, risk controls, and execution.

You will collaborate with researchers and traders to turn strategy requirements into robust software while maintaining latency, determinism, and operational risk considerations.