AI-Driven Quant Developer for Low-Latency Trading

JPMorgan Chase & Co.; City of Rochester (NY); On-site; USD 180,000 - 260,000; Full time

Job summary

JPMorgan Chase & Co. in New York/Global AI Market Lab seeks engineers to build AI-driven systematic trading platforms. You’ll bridge quantitative research, low-latency engineering, and ML infrastructure to create reliable production systems for monitored, deterministic strategies.

This role emphasizes turning ambiguous research into fast, clean interfaces and reproducible workflows while handling latency, determinism, and operational risk in live trading environments.

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++ development

Python

Distributed systems

Low-latency engineering

Performance profiling

Software design

Production debugging

ML infrastructure

Education

Bachelor’s/Master’s/PhD in Computer Science, Engineering, Mathematics

Tools

PyTorch

JAX

CUDA

GPU clusters

Ray

Kafka

Kubernetes

Spark

Job description

JPMorgan Chase & Co. in New York/Global AI Market Lab seeks engineers to build AI-driven systematic trading platforms. You’ll bridge quantitative research, low-latency engineering, and ML infrastructure to create reliable production systems for monitored, deterministic strategies.

This role emphasizes turning ambiguous research into fast, clean interfaces and reproducible workflows while handling latency, determinism, and operational risk in live trading environments.