AI-Driven Quantitative Trading Engineer

Next Frontier Capital; Worcester (MA); On-site; USD 140,000 - 220,000; Full time

Job summary

J.P. Morgan’s Quantitative Trading & Research group seeks a quantitative developer to build research and production tech for AI-driven systematic trading.

You will work at the boundary of research, low-latency engineering, and ML infrastructure to create reliable platforms that move from data and prototypes to production strategies. The role emphasizes turning ambiguous requirements into fast, deterministic systems while managing latency, risk, and operational realities in a global trading

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 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

Low-latency engineering

Education

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

Tools

PyTorch

JAX

CUDA

Kafka

Kubernetes

Spark

Job description

J.P. Morgan’s Quantitative Trading & Research group seeks a quantitative developer to build research and production tech for AI-driven systematic trading.

You will work at the boundary of research, low-latency engineering, and ML infrastructure to create reliable platforms that move from data and prototypes to production strategies. The role emphasizes turning ambiguous requirements into fast, deterministic systems while managing latency, risk, and operational realities in a global trading