Quantitative Trading & Research - Quantitative Developer - Associate or Vice President
Join a pioneering team at the forefront of systematic trading innovation. The Quantitative Trading & Research (QTR) group is responsible for systematic trading across FX, Rates, Commodities, Credit, Equity and a wide range of markets. Within QTR, AI Market Lab brings together quantitative research, modern artificial intelligence, market microstructure, and high-performance engineering to develop the next generation of electronic trading capabilities. Our work spans signal research, pricing, market making, execution, portfolio construction, risk management, and the production systems that support them.
Job Summary
As a Quantitative Trading & Research – Quantitative developer in the AI Market Lab, 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. We are seeking strong talent to build the research and production technology behind AI-driven systematic trading.
This role is ideal for engineers who enjoy turning ambiguous research requirements into clean interfaces, fast systems, and reproducible workflows—without losing sight of trading realities like latency, determinism, and operational risk.
Job 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.
Required Qualifications, Capabilities, and Skills
- Bachelor’s, Master’s, or PhD in computer science, engineering, mathematics, or a related technical discipline (or equivalent professional experience).
- Relevant professional experience in software engineering, quantitative development, low-latency systems, or ML infrastructure.
- Strong modern C++ skills in 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 to incident resolution.
Preferred Qualifications, Capabilities, and Skills
- Experience with electronic trading architecture: exchange connectivity, market-data normalization, order management, pre-trade risk, or execution systems.
- Knowledge of Linux performance engineering: kernel/network tuning, lock-free programming, hardware-aware optimization, or FPGA-adjacent systems.
- Experience with ML/data tooling such as PyTorch, JAX, CUDA, GPU clusters, Ray, Kafka, Kubernetes, Spark, or comparable technologies.
- Understanding of market microstructure, backtesting pitfalls, transaction costs, and the operational needs of live quantitative strategies.
- Experience in environments operating real-time systems (hedge fund, proprietary trading firm, market maker, exchange, or financial institution).
Skills Required
- Bachelor's, Master's, or PhD in computer science, engineering, mathematics, or a related technical discipline, or equivalent professional experience
- Relevant professional experience in software engineering, quantitative development, low-latency systems, or ML infrastructure
- Strong modern C++ skills in 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
- Understanding of distributed systems, testing, software design, reliability, and operating production services end-to-end
- Experience owning performance-critical systems from design and deployment through monitoring and incident resolution
- Experience with electronic trading architecture, including exchange connectivity, market-data normalization, order management, pre-trade risk, or execution systems
- Knowledge of Linux performance engineering, kernel or network tuning, lock-free programming, hardware-aware optimization, or FPGA-adjacent systems
- Experience with ML and data tooling such as PyTorch, JAX, CUDA, GPU clusters, Ray, Kafka, Kubernetes, or Spark
- Understanding of market microstructure, backtesting pitfalls, transaction costs, and operational requirements of live quantitative strategies
- Experience operating real-time systems in a hedge fund, proprietary trading firm, market maker, exchange, or financial institution
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
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Parental & Family Support — Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
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Retirement Support — Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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