Senior Python Developer using Python and AWS to design, develop and enhance high performance trading systems and cloud infrastructure supporting front, middle and back office operations on the Asset Management side of a global Japanese bank.

Hudson River Trading★4.5 (2)· London

You will work with Python, Pandas, NumPy, R, and MATLAB to apply statistical analysis and machine learning to vast quantities of market data. The team builds and maintains predictive trading models for the company's high-performance trading infrastructure. You will research, develop, and test order execution methods to increase trading efficiency.

Hudson River Trading★4.5 (2)· London

You will use Python, C++, Pandas, NumPy, R, or MATLAB to build and maintain predictive trading models. As an algorithm developer, you research and test novel order execution and model training methods, applying

Hudson River Trading★4.5 (2)· London

You will write and maintain critical trading infrastructure using C/C++ or Python on Linux, working closely with engineers who design trading algorithms in a fast-paced, real-time environment. The role is with Hudson River Trading, a firm that brings a scientific approach to trading financial products.

Hudson River Trading★4.5 (2)· London

Software engineering interns work with Python, C, or C++ on independent programming projects and gain hands-on exposure to HRT's algorithmic trading research and infrastructure.

Software engineers use OCaml (primary) and sometimes Python, along with internal libraries and tools. The intern works on real projects ranging from high-performance trading systems to programming language design.

Senior Data Engineer at Softwire, a UK digital consultancy, working with Python, SQL, Databricks, Snowflake, Fabric, and AWS/Azure/GCP across data architecture, pipeline design, and governance. You'll lead complex data engineering projects for clients across public and private sectors—from healthcare research platforms to energy market infrastructure—while mentoring junior engineers and shaping technical direction on multi-stakeholder engagements.

Société Générale★3.8 (3.8k)· London

Support Windows/Linux, SQL, Python, or C# while monitoring and troubleshooting critical trading applications used by foreign exchange and fixed income teams. You'll assist traders and sales desks, resolve technical issues, and contribute to system improvements within Société Générale's Trading Technology team.

Design and build low-latency FX trading systems at Citi, working hands-on with traders and quant teams to replace legacy systems and design new architecture. You will use your systems-level knowledge (software, hardware, networks) to define solutions and troubleshoot issues.

Develop core eTrading MI & Analytics platform components using q and kdb+, with CI/CD, TDD/BDD, and an additional programming language. The platform captures, stores, and analyses over 3TB/5 billion daily records from electronic trading venues for risk, quant, trading, and sales stakeholders.

Python micro-services with RabbitMQ and OpenShift/Kubernetes, using SQL Server and Parquet. The London Commodities Risk Technology team builds a front-office distributed platform for trading and risk calculations on assets like oil, gas, power, and exotics, collaborating with traders and quants.

You will work with Python, JavaScript, SQL, Kafka, AWS/Azure, PostgreSQL, SQL Server, ClickHouse, and MongoDB. The team designs and delivers real-time, high-performance trading systems for Energy & Commodities, integrating market data, risk, and front-to-back office workflows.

Build high-performance front ends with React, TypeScript, JavaScript, React Hooks, and ES6/ES7 for a leading HFT firm in London. The role focuses on UI engineering within a trading environment.

You will design, implement and maintain high-frequency trading systems using C++ and ultra-low-latency technology. The role is with a new HFT built out of an established systematic fund, trading multiple asset classes across international markets. You join a small team working on greenfield projects with no red tape.

Python and C++ (C++17 or later), SQL, and Linux. The team builds and enhances a cutting-edge quantitative trading platform for a world-leading hedge fund, working alongside senior PMs, quants, and engineers across major financial markets.

You'll use modern C++ (Python a plus) to develop an ultra-low-latency trading engine, research platform, and cloud analytics infrastructure for a systematic quant hedge fund. Working directly on a trading desk with traders and researchers, you'll own projects end-to-end and tackle hard technical challenges critical to desk success.

You will use C/C++, STL, Boost, and Linux to build low-latency algorithmic trading systems. The team develops and supports all aspects of trading strategies, including exchange price feeds, back testing, and production environments for a tech-driven quantitative hedge fund.

Develop, optimize and maintain high-performance C++ code for ultra-low-latency trading systems, working on strategy interaction with FPGA. Collaborate with infrastructure and network teams. Requires deep metaprogramming and 7+ years' C++ experience, with knowledge of memory management, multithreading, CPU cache optimization, and Linux.

You’ll work with modern C++, Python, and systems-level knowledge of CPU, memory, OS, and networking. As part of a trading-desk Quant Dev team collaborating with researchers and traders, you’ll build ultra-low-latency trading engines, research platforms handling terabytes of daily data, and cloud-based analytics infrastructure for a global systematic hedge fund.

The role involves developing and maintaining in-house C++ pricing libraries, multi-threaded servers, and automated trading systems, while advancing the quantitative toolbox with new algorithms. You will work on model frameworks, signal research, execution and portfolio construction tools, using Python and C++ with QuantLib experience preferred.

C++ developers will work on ultra-low-latency exchange protocol encoders and automated trading strategies, using C++ and optionally Python, for a data-driven prop fund’s global automated trading systems. The role involves collaborating with researchers and ops in a small, fast-paced team operating in a real-time environment.

This hands-on Lead Pricing Engineer role uses Java and ultra-low-latency development for Citi's FX eTrading pricing team. The team defines and implements solutions for multiple asset classes within the largest global FX bank. The position includes managing a high-quality team of engineers.

You will work with Rust, Java, C++, KDB, event-sourcing microservices, Linux, TCP, and kernel-bypass networking (Solarflare OpenOnload). The High Performance Architectures team builds low-latency application frameworks and supports modernisation for over 100 eTrading teams across Citi.

Build microservices-based event sourcing systems on an in-house low-latency framework using Java, Rust, C++, KDB, and market data technologies within Citi’s London High Performance Architectures team. The team provides application frameworks and modernization support to over 100 teams, with a focus on low-latency algorithmic trading platforms in Markets Technology.

You will work with Core Java, Aeron, FIX, SBE, Artio, Linux, and performance profiling tools. You will join a team developing a high-performance electronic trading platform with a focus on microsecond-level latency. The role requires 5+ years of Core Java experience and 2+ years in ultra-low-latency systems.