AI-Driven Quant Trading & Research Engineer

JPMorganChase; New York (NY); On-site; USD 180,000 - 320,000; Full time

Job summary

JPMorganChase in New York is seeking an Associate or Vice President 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, 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++

Python

Distributed systems

Performance ownership

Education

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

Tools

PyTorch

JAX

CUDA

GPU clusters

Ray

Kafka

Kubernetes

Spark

Job description

JPMorganChase in New York is seeking an Associate or Vice President 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