You will work with Python, Bash, and possibly simple C++ changes/deployment. You will join the market access team to build and support systems that interface with markets, brokers, and data providers for a tech-driven quant 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.

Builds cloud platforms for a systematic quant hedge fund's trading and research, using AWS (EC2, S3, VPC), Python/Bash, Jenkins/GitLab CI, Terraform/CloudFormation/AWS CDK, Docker, and Kubernetes to support digital asset and crypto systems.

You will work with Linux, AWS, Docker, Kubernetes, CI/CD pipelines, Python, Bash, and monitoring tools like Datadog, Prometheus, CloudWatch, or ELK. You will support and maintain the critical research and trading infrastructure for a quantitative hedge fund, acting as first-line support for platform-related issues.

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.

Hudson River Trading★4.5 (2)· London

You will use Ansible, Terraform, Microsoft Graph API, PowerShell, Microsoft Intune, Autopilot, Entra ID, and Active Directory to build configuration-as-code and infrastructure-as-code solutions. You will help scale HRT’s global hybrid Windows deployment, managing user endpoints, mission-critical servers, cloud infrastructure, and secure remote computing environments. This role is on the Enterprise Engineering team.

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.

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.

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.

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

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.

You'll operate vulnerability scanning tools across on-premise, cloud, and hybrid environments, using scripting/automation (e.g., Python, PowerShell). You join Qube Research & Technologies, a global quantitative and systematic investment manager, working within the security function to run the vulnerability management programme across infrastructure and cloud.

Hudson River Trading★4.5 (2)· London

Work with Linux, SaltStack, Python, bash, and JIRA to design, automate, and optimize worldwide trading infrastructure. The team builds and maintains ultra low-latency operating systems and automation software that power HRT’s global 24/7 trading.

Hudson River Trading★4.5 (2)· London

Work with Linux systems (Debian/Ubuntu), SaltStack, shell (bash) scripting, JIRA, and TCP/IP networking on infrastructure supporting ultra low-latency trading. The team builds and maintains the production trading environment, managing hardware, kernel, and applications for global 24/7 operations.

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.

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.

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.

You will work with C++, Rust, Python, TypeScript, and protocols like FIX, WebSocket, and HTTP to build ultra-low-latency event-driven trading systems. The team develops Flow Traders' proprietary trading platform, covering venue connectivity, trading engines, and shared platforms for high-frequency trading across hundreds of global venues.

Tower Research Capital★4.1 (12)· London

You will support and maintain Tower Research Capital's Linux infrastructure for high-frequency, low-latency electronic trading systems, working with technologies including AWS (EC2, VPC, ELB, S3, EBS), Ansible, Python, Bash, Docker, and Kubernetes. Responsibilities include managing core services (DHCP, LDAP, DNS, NFS), automating provisioning and monitoring across thousands of servers in on-premises and cloud environments, and participating in on-call rotations supporting 24/7 critical trading infrastructure. You'll need at least five years of Linux administration experience, deep knowledge of OS internals and networking, and expertise in infrastructure automation and CI/CD practices.

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.