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.

Work with modern C++ (C++17/20, template metaprogramming), network programming, distributed computing, and Unix/Linux. You will design and build efficient code for the production trading and research system within a newly formed Low Latency Trading group at a systematic hedge fund.

Work with Terraform, Ansible, Kubernetes, Python, Bash, Go, Jenkins, GitHub Actions, Prometheus, and Grafana to build infrastructure automation platforms supporting python-based quantitative research and trading systems. Manage on-premises resources across Ubuntu and Windows Server environments.

Work with C++, Python, Unix, and git in a quant fund's crypto division. You will build and optimize trading strategies, research new protocols and data sources, and design and improve research and trading systems.

You'll work with C# and .NET as core systems, plus Python across quant and data groups, and may use other OO languages. The role involves designing and building high-impact trading and research platforms for a fixed-income hedge fund's front-office engineering team.

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.

Durlston Partners· London

You'll use Java, Spring Boot, Kafka, and AWS (EKS, S3), plus PostgreSQL, SQL Server, and CI/CD. The team builds the core trade processing, reconciliation, and reporting platform for a leading systematic hedge fund’s multi-asset trading, collaborating closely with traders and quants.

As a Kdb+/Q Engineer at Citadel Securities, you will design and build high-performance data and analytics platforms using Kdb+/Q, Python/Java/C++, and Linux/distributed systems for real-time and historical market data that power trading and quantitative research globally. You will collaborate with traders, researchers, and engineers on scalable solutions for large-scale market data and time-series analytics.

You will use Python, C++, Linux/UNIX, PyTorch, JAX, or TensorFlow to develop and deploy advanced ML models (Deep Learning, Reinforcement Learning, sequence models) for forecasting asset volatility. Part of a specialized research team, you will perform greenfield research on unstructured datasets to discover new alpha signals for trading at a systematic investment firm.

Work with Python, Java, C++, Linux, and kernel-bypass networking. You will develop and maintain infrastructure for low-latency market data delivery and order execution across global exchanges, supporting multiple trading desks at a quantitative investment management firm.

Develop trading algorithm implementations, options pricing, volatility calculations, and simulation frameworks in Java 21+ and Python. You will collaborate with traders, researchers, and quants on high-impact projects for IMC, a global trading firm.

BlackRock★3.8 (632)· London

Build and maintain equity risk models using Python within the Aladdin Financial Engineering team, which develops financial models for risk management analytics used by BlackRock and its clients. This role also contributes to applying AI and automation to modernize workflows.

Will work with KDB+/q, real-time data ingestion, historical databases, and Linux/Unix scripting to build platforms for Commodities and Global Markets, supporting Quantitative Investment Strategies with market data for trading, risk, and research across multi-asset products including commodities, options, futures, and indices. Joins a small, hands-on team modernising the KDB ecosystem with cloud migration and AI.

KDB+/q, Python, and Linux/Unix. Builds and optimises real-time data platforms supporting systematic trading, quantitative research, and investment decision-making for a global investment firm.

You will use modern C++ and Linux to develop and optimize low-latency trading infrastructure and distributed systems. The team builds market data, order entry, and execution systems for global financial markets, supporting real-time trading and quantitative research. You collaborate closely with traders and researchers.

Jump Trading★3.8 (11)· London

Work with Linux/UNIX, shell scripts, Python, and networking concepts like routing, multicast, and ethernet. You will join Trading Infrastructure to architect, build, and maintain low-latency trading platforms, including colo design and exchange connectivity.

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.

Jump Trading★3.8 (11)· London

Systems Engineers at Jump Trading work with Linux/UNIX, Python, and networking technologies (routing, multicast, ethernet) to build automation and optimize infrastructure. They monitor, analyze, and troubleshoot the trading platform, which supports Jump’s high-frequency trading operations in global data centers. This is an individual contributor role without a stated team size.

You will work primarily with C# and .NET, alongside Python used by quant and data groups. You will design, build, and enhance high‑impact trading and research platforms for a leading fixed income hedge fund, covering core trading systems and front‑office tooling.

Castleton Commodities International★3.2 (24)· London

The engineer will work with Python, React, Angular, TypeScript, AWS, Snowflake, and CI/CD to build cloud-native tools for the front office. The team develops real-time analytics, backtesting engines, and market analysis tools to support energy commodity trading and risk management.

Point72★3.6 (15)· London

You'll work with large datasets using languages like Python, C++, Java, R, or MATLAB to preprocess data and build predictive models for market dynamics and systematic trading. Point72 is a quantitative investment firm applying advanced statistical learning to market prediction. This internship involves feature engineering and data validation for model estimation across a small team environment.

Point72★3.6 (15)· London

Cubist Systematic Strategies, Point72's affiliate, seeks quantitative researchers to develop statistical and predictive models for systematic trading across equities, futures, and foreign exchange using languages including Python, C++, Java, R, and MATLAB. Researchers will independently conduct rigorous research into market anomalies, managing methodology selection, data collection, backtesting, and performance monitoring. Candidates should have 3-7 years of alpha-driven quantitative research experience and advanced degrees in finance, computer science, mathematics, physics, or related quantitative disciplines.

Goldman Sachs★3.9 (2.3k)· London

You will develop quantitative trading and market making strategies across Fixed Income, Currencies, and Commodities (FICC) products using C++, Java, or Python alongside advanced statistical analysis, machine learning, and neural networks. The role involves building pricing and risk management models, collaborating with Quant Developers and trading teams, and deploying systematic alpha strategies across interest rates, FX, credit, and commodities at Goldman Sachs' London trading desk.

LSEG★3.7 (402)· London

FTSE Russell seeks a Quantitative Engineer to build scalable applications supporting index calculations, back-testing, and analytics using Python, SQL, numpy, pandas, scipy, and cloud-native solutions with RESTful APIs and CI/CD pipelines. The role combines software engineering with quantitative finance to develop tools for index monitoring, validation, and rebalancing across equity, fixed-income, currencies, and commodities. Requires 2+ years in quantitative analytics within financial services and an advanced degree in Mathematics, Computer Science, Financial Engineering, Statistics, or Physics.