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$122,800–$187,500.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
Quantitative Trading & Research - Quantitative Developer Systematic Trading - Associate joins the AI Market Lab to build research and production technology for AI-driven systematic trading. This role focuses on developing high-performance components including market data, feature computation, backtesting, simulation, model serving, execution, and monitoring systems. The developer will create low-latency C++ services and APIs that integrate quantitative models with real-time pricing and risk controls while building scalable data pipelines for reproducible experiments. Key technical requirements include proficiency in modern C++, Python, and distributed systems, alongside experience with PyTorch, JAX, CUDA, Ray, Kafka, Kubernetes, or Spark. The role addresses the challenge of translating research prototypes into resilient production strategies by managing market microstructure complexities, ensuring deterministic behavior, and optimizing critical paths for throughput and memory efficiency across various asset classes like FX, Rates, Commodities, Credit, and Equity.
Build high-performance components for market data, feature computation, backtesting, and execution monitoring.
Develop low-latency C++ services to integrate quantitative models with real-time market data and risk controls.
Create scalable data pipelines to support historical data analysis and reproducible research experiments.
Optimize critical system paths for throughput, tail latency, memory efficiency, and deterministic behavior.
Productionize machine learning models by building training workflows, inference systems, and deployment automation.
Translate complex trading strategy requirements into robust software and reliable production systems.
What we're looking for
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 including 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 through deployment, monitoring, and incident resolution.
Experience with electronic trading architecture such as exchange connectivity, market-data normalization, order management, pre-trade risk, or execution systems (preferred).
Knowledge of Linux performance engineering, ML/data tooling, and understanding of market microstructure (preferred).
Python
KDB
C++
Java
Machine Learning
Data Analytics
Statistical Modeling
Backtesting
Risk Management
Derivatives Pricing
Feature Engineering
Signal Research
Software Engineering
AI
Transformer
PyTorch
JAX
Machine Learning
Distributed Training
Quantitative Trading
Data Pipelines
Signal Research
Market Microstructure
Portfolio Construction
Risk Management
Benchmarking