AI-Driven Quantitative Trading Engineer (Low-Latency)

J.P. Morgan; Worcester (MA); On-site; USD 150,000 - 230,000; Full time

Job summary

J.P. Morgan is seeking a quantitative developer to bridge research and production for AI-driven systematic trading. You will design high-performance, low-latency components that integrate models with real-time data and trading systems.

You will collaborate with researchers and traders to turn ambiguous requirements into clean interfaces, robust services, and reproducible workflows while managing latency, determinism, and operational risk across production environments.

Qualifications

• Bachelor’s, Master’s, or PhD in computer science, engineering, mathematics, or related field.
• 2+ years of professional software engineering, quantitative development, or ML infra.
• Strong modern C++ skills: data structures, concurrency, memory management.
• Proficiency in Python and software for quantitative researchers or data apps.
• Understanding of distributed systems, testing, reliability, end-to-end operations.
• Ownership of performance-critical systems from design to incident resolution.

Responsibilities

• Design and build high-performance market-data, feature, backtesting, and monitoring components for systematic trading.
• Develop low-latency C++ services integrating models with real-time data and order-management systems.
• Build scalable data and research pipelines for historical data, experiments, and distributed compute.
• Optimize paths for throughput, tail latency, memory use, resilience, and determinism with profiling.
• Productionize ML models including training, versioning, real-time inference, and deployment.
• Collaborate with researchers and traders to translate requirements into robust software and live systems.

Skills

C++ programming

Python proficiency

Distributed systems

Low-latency design

ML infrastructure

Software engineering

Education

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

Tools

PyTorch

JAX

CUDA

Kafka

Kubernetes

Spark

Job description

J.P. Morgan is seeking a quantitative developer to bridge research and production for AI-driven systematic trading. You will design high-performance, low-latency components that integrate models with real-time data and trading systems.

You will collaborate with researchers and traders to turn ambiguous requirements into clean interfaces, robust services, and reproducible workflows while managing latency, determinism, and operational risk across production environments.