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.

Goldman Sachs★3.9 (2.3k)· London

Build a high-performance, low-latency data platform for post-trade processing using Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala. You will own the full lifecycle of core systems, designing distributed computation and an AI-powered UI/agent framework to deliver intelligent analytics over large-scale business data.

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

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.

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 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.

Morgan McKinley★3.8 (45)· London

You’ll work with modern Java, JVM internals, Linux, low-latency messaging (Aeron, Chronicle Queue, Kafka, ZeroMQ), Netty, SBE, FIX/FIXP, and profiling tools to build event-sourced microservices for FX and cash equities electronic trading. The employer is a technical vendor handling mission-critical engagements for a tier-1 client’s trading desks. No team size is stated.

You will work with C++, Python, Rust, React, and kdb+ to design and build high-performance, scalable software solutions for a market-leading technology business. The role involves writing production code, collaborating on code reviews, and solving complex technical challenges.

Develop KDB+/q applications for real-time market data and scalable infrastructure supporting quantitative strategies at a leading global hedge fund. You will build high-performance research, analytics, and trading platforms, working with Quants and Traders to solve low-latency engineering challenges.

Work with advanced Python, large complex datasets, and a proprietary technology stack including high-performance trading systems and data platforms. As a Quantitative Researcher, you will lead independent research to discover and deploy alpha-generating systematic investment strategies across global equity markets.

Uses Python, SQL, Pandas, NumPy, SciPy, Scikit-learn, PyTorch/TensorFlow, Git, Linux, and cloud computing. Researches and develops alpha signals, systematic strategies, and portfolio construction for global equity markets at a systematic trading firm.

Use Python, FastAPI, Postgres, Redis, Docker/Kubernetes, and AWS to design and deploy high-performance APIs and backend services for electronic commodity trading platforms as a founding member of the company's new London engineering hub.

Durlston Partners· London

Java, distributed systems, and production-grade applications. You will build and maintain core systems supporting trading and research at a systematic hedge fund. You join a small, high-calibre engineering team with end-to-end feature ownership.

Use Python, LLMs, agentic frameworks, MCP servers, RAG, and REST APIs to design and deploy production-grade AI systems. You will define the AI roadmap for a global investment firm, building tools that directly impact research, trading, and business decisions. The role works with Portfolio Managers, quants, and senior leadership.

Work with Java (including JDK migration), Kotlin, Python, Kubernetes, ArgoCD, OpenTelemetry, and modern CI/CD pipelines to develop and maintain distributed services for ingesting and processing financial market reference data. You will modernize critical production systems, including a large-scale Java/JDK upgrade programme and improvements to platform reliability and cloud-native infrastructure.

Quantitative Researchers at Jane Street build models, strategies, and systems for pricing and trading financial instruments, working with Python, petabytes of data, and a large GPU cluster. They apply statistical and ML techniques, from linear models to deep learning.

Founding Engineers own the full stack: Python, C++/Rust (bonus), and production data pipelines. They build risk models, backtesting infrastructure, scenario tools, and an AI-driven research layer on massive financial datasets. The team owns entire systems—from math and data to APIs and interfaces—for a live fintech serving professional investors.

You will work with Python, Angular/React, SQL/NoSQL databases, CI/CD, and cloud environments. The role involves designing scalable applications for trading, structuring, and risk, contributing to a centralised quantitative platform used across multiple desks.

You will work across the full stack with React, Node.js, and JavaScript, building high-performance UIs and services for real-time equities data. The product is a core trading platform handling billions of dollars in daily flow, used by front-office traders in London, Chicago, and Hong Kong.

Design, write, and maintain Python infrastructure and work with Linux (C++ preferable) on a quantitative trading team at a high-frequency trading firm, focusing on high-throughput, low-latency automated electronic trading systems.

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.

You will work with C#, .NET, SQL Server, and ASP.NET to build greenfield trading and research systems. The team develops high-performance applications that support automated trading strategies and real-world trading.

Work with modern C++ (C++17 or later) and potentially Python to develop commodities quantitative models for risk, portfolio management, and derivatives modeling (VaR, forward curves, volatility surfaces) at a global hedge fund. Focus on greenfield projects in commodities markets.

You will use Python (pandas, NumPy, SciPy, matplotlib/seaborn), SQL, and Azure cloud tools to build predictive models and develop reproducible data science processes alongside a team of investment professionals at a UK investment management company.

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.