Python, C++, KDB+/q, Git, Agile, CI/CD, and database technologies. You will partner with Quantitative Researchers to build scalable Python applications and high-performance data processing for research, analytics, and live trading at a hedge fund.

JPMorgan★3.9 (20k)· London

Lead projects on the Strategic Index Technology team, using Python, Java, C++, or C# to build and maintain the cross-markets index platform alongside Quantitative Research, Trading, and Sales.

You will work with Go and/or Python, plus Kubernetes, Docker, and cloud infrastructure. You'll support a systematic cryptocurrency trading team by maintaining live production trading and research systems, and helping to deploy strategies.

Python, SQL, Git, and logging/monitoring tooling for distributed systems and large-scale data processing. The Quant Developer builds scalable research and trading platforms alongside quantitative researchers in a global systematic hedge fund.

Jump Trading★3.8 (11)· London

You will use advanced TypeScript, Python, and modern Web frameworks to build Web-based applications interacting with Jump Trading’s real-time trading platform. The Core Development team architects and maintains the firm’s world-class trading platform.

Jump Trading★3.8 (11)· London

A 10-week internship working with Python on Linux, building and maintaining data pipelines and infrastructure for Jump Trading's proprietary trading platform, using Agile development and production code.

Jump Trading★3.8 (11)· London

As a core development intern, you will design, code and test the firm's distributed trading system using C++ and Python on Linux, with Git for version control, and gain experience with Agile methodologies. The team builds and maintains Jump Trading's world-class low-latency trading platform and infrastructure.

JPMorgan★3.9 (20k)· London

As a Lead Software Engineer on the Rates Nonlinear Marking and Pricing team, you will use Python to design and deliver real-time marking, pricing, and market data platforms that power the Rates Nonlinear franchise. You will work with front office traders and quantitative research, driving the technical agenda for the EMEA region on the full trade lifecycle. You will also drive adoption of enterprise-authorized AI-assisted engineering practices.

You will work with Python, TypeScript, AWS (Cognito, Lambda, Fargate, API Gateway, S3, IAM), Terraform, PostgreSQL, and AI tools (Claude, GitHub Copilot, Cursor, LLM APIs). The team builds and evolves scalable microservices for BMLL Lab & Vantage, the company’s SaaS products for data science and visualisation on large financial datasets.

LSEG★3.7 (402)· London

You will develop and maintain quantitative research platforms using Python, SQL, CI/CD, cloud computing, and AI-assisted development tools while building AI-enabled workflows for index analytics and research efficiency. The Index Research & Design team at FTSE Russell creates equity and multi-asset index methodologies and analytical solutions used across global financial markets. You will manage research priorities across analytics, software development, data quality and client engagement, partnering with Research, Engineering, Product and Sales teams.

Citi★3.9 (21k)· London

You'll design and build Citi's next-generation algorithmic trading and Smart Order Routing platform using low-latency Java or Rust, collaborating with trading desks and quantitative researchers. The role involves hands-on development, architectural decisions, automated testing frameworks, and CI/CD implementation while optimizing for performance and latency across global markets. Prior experience in algorithmic trading, SOR platforms, or quantitative trading in financial institutions is required, along with expertise in low-latency system design and market microstructure knowledge.

JPMorgan★3.9 (20k)· London

You'll work with Java, low-latency real-time systems, high-throughput messaging APIs, and middleware to design and develop equities algorithmic trading strategies and execution platforms. You'll collaborate with quants, traders, and technologists globally at JPMorgan's Electronic Client Services desk—a market-leading agency flow execution provider—developing simulation environments, enhancing strategies, and maintaining the trading engine across multiple technical areas.

JPMorgan★3.9 (20k)· London

You'll work with Python, KDB/C++, and AI technologies to design and optimize real-time data processing pipelines for JPMorgan's Electronic Trading Technology team within Commercial & Investment Bank. You'll lead technical initiatives across global analytics teams, building scalable solutions for mission-critical trading and research systems while mentoring engineers and driving SDLC improvements. This is a leadership role managing distributed teams in a fast-paced financial environment.

JPMorgan★3.9 (20k)· London

You'll develop and maintain a market-leading equities algo execution platform using Java, focusing on low-latency real-time trading systems, high-throughput messaging APIs, and simulation environments. Working across JPMorgan's Electronic Client Services desk—the top EMEA agency flow provider—you'll collaborate globally with quants, traders, and technologists on trading engine infrastructure, quantitative models, and strategy optimization. This VP-level leadership role involves designing algo strategies, enhancing performance through analytics, and driving operational stability across the global platform.

JPMorgan★3.9 (20k)· London

You'll write Python for JPMorgan's equities prime services front-office trading systems, collaborating with traders and quantitative researchers on pre-trade analytics, execution algorithms, and post-trade analysis. Required skills include 5+ years software engineering experience, deep capital markets knowledge, electronic trading workflow expertise, and advanced Python proficiency. KDB/q, FIX, market data systems, and data streaming frameworks like Kafka are preferred.

Flow Traders, a proprietary trading firm, seeks a Senior Research Engineer to lead development of their trading model research framework using Python, PyTorch, Polars, Pandas, Ray, AWS/Azure/GCP, Docker, and Kubernetes. You'll design end-to-end ML pipelines for training and deploying trading models in production, then partner with Quantitative Researchers to develop data-driven systematic trading strategies and alpha signals.

Hudson River Trading★4.5 (2)· London

You'll build backend processes and UIs using Python and React for Hudson River Trading's trading and research infrastructure. Work on either the platform team supporting distributed-compute frameworks for model training across the compute cluster, or the acceleration team building trading oversight tools, risk assessment dashboards, and strategy research capabilities directly with algo developers and traders.