JPMorganChase Logo

JPMorganChase

Quantitative Trading & Research - Quantitative Developer - Associate or Vice President

Posted An Hour Ago
Be an Early Applicant
Hybrid
London, Greater London, England, GBR
Entry level
Hybrid
London, Greater London, England, GBR
Entry level
Build high-performance quantitative trading infrastructure, including market-data, backtesting, simulation, model-serving, execution, and monitoring systems. Develop low-latency C++ services and scalable Python research pipelines, optimize throughput and latency, productionize machine-learning models, and partner with researchers and traders to deploy reliable live trading strategies.
The summary above was generated by AI

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).
About UsJ.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
  
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
About the TeamJ.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. 

JPMorganChase London, England Office

25 Bank Street, Canary Wharf, London, United Kingdom, E14 5JP

Similar Jobs

Senior level
Financial Services
Design, develop and optimize a large-scale Monte Carlo engine for CVA/FVA calculations; implement numerical techniques for efficiency; build production-grade analytics; collaborate with traders, risk managers and tech teams; drive software engineering best practices.
Top Skills: Adjoint Analytic Differentiation (Aad)AIMachine LearningMonte Carlo SimulationPython
33 Minutes Ago
Hybrid
London, Greater London, England, GBR
Senior level
Senior level
Fintech • Mobile • Payments • Software • Financial Services
Leads the Finance Tribe’s product strategy and a team of Product and Implementation Managers. The role oversees ERP selection and implementation, finance systems and data products, finance process automation, SOX compliance tooling, auditability, financial controls, and improvements to financial close and reporting. The Product Lead works cross-functionally with engineering, finance, operations, analytics, data science, and senior business leaders while coaching product managers and driving complex global fintech initiatives.
Top Skills: AIOracleSAP
34 Minutes Ago
Hybrid
London, Greater London, England, GBR
Expert/Leader
Expert/Leader
Fintech • Mobile • Payments • Software • Financial Services
Principal Product Manager responsible for shaping Wise’s Cash & Asset Management and Counterparty Credit Risk product domains. The role owns product strategy, systems, controls, metrics, vendor evaluation, and operating models governing a roughly £20 billion customer-funds portfolio. It requires alignment across engineering, analytics, treasury, risk, and regional stakeholders while balancing yield, liquidity, capital, customer outcomes, and counterparty risk at global scale.

What you need to know about the London Tech Scene

London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account