Full-stack Java development on Linux/Unix, using AI coding tools like Claude Code, Windsurf, Devin, or GitHub Copilot. The role is for Ascendion, a technology services company.

The role involves developing embedded software and software for high-speed network platforms, working with GPU-based infrastructure and interconnect technologies. The company builds next-generation networking solutions integrating hardware and photonics for high-performance computing systems.

You will work with C++, Linux, and real-time frameworks to design, develop, integrate, and verify software for high-performance real-time systems. The team builds and supports advanced test and data capture systems for the defence sector.

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.

Linux Engineers at Jane Street work with on-prem and cloud infrastructure, Linux, Nix, RPMs, and open-source tools across compute, storage, and networking. The role maintains the critical infrastructure underlying the firm’s technology, building in-house tools and automating systems.

This IT Operations internship at Jane Street involves hands-on support, configuration, and operation of systems across desktop engineering, network, and application platforms. You'll build and configure Windows and Linux devices, support Windows domain infrastructure, monitor systems, and use tools like PowerShell. The role requires knowledge of Windows and computer hardware, with scripting familiarity (PowerShell or Bash) a plus.

DeepL★3.8 (4)· London

Work with Kubernetes, Terraform, ArgoCD, Go or Python, and AWS across hybrid on-prem and cloud infrastructure. The Hybrid Platform Engineering track builds and operates the compute layer—Kubernetes control plane, networking, storage, and core services—powering DeepL's language AI products and research. The role involves deepening the hybrid model and unifying workloads across on-prem and AWS.

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.

Senior Machine Learning Engineer at ASOS, building production ML systems for personalized outfit recommendations and style discovery. You'll work with deep learning frameworks like PyTorch/TensorFlow, distributed GPU infrastructure, and MLOps practices including CI/CD, containerization, and observability. Collaborate with ML Scientists on batch and real-time models serving millions of customers.

Use deep learning frameworks, distributed computing, GPU-based training, and MLOps to build and deploy batch and real-time ML models. The Search & Recommendations team develops personalised recommendations, product ranking, and AI styling experiences for ASOS's online fashion platform, helping customers discover products.

You’ll train ML models, work on ML libraries and workflows, and use a GPU cluster with H100/H200/B200s. Projects are real-world machine learning applications for Jane Street’s global trading business, testing ideas against noisy financial data. No team size is stated.

You'll work across the full stack using Python, frontend, embedded systems, ML, and networking, with Linux, devops, and edge-device deployment. Minerva Defence builds software, hardware, and networking for unmanned battlefield systems.

This DevOps traineeship covers Linux, Git, Docker, container orchestration, AWS, Azure, Google Cloud, CI/CD, shell scripting, IaC, configuration management, monitoring, networking, and DevSecOps. It provides hands-on experience through realistic projects such as building CI/CD pipelines, deploying applications, managing containers, and automating processes, with no prior experience required.

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.

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 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.

You will work with C++, Python, Linux, machine-learning libraries, Google Cloud, Airflow, InfluxDB, and Grafana. This role builds data engineering and prediction tools for systematic equity trading, developing software for quantitative research, maintaining data pipelines, and implementing large-scale computation and serialization frameworks.

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 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.

Work with C# on .Net Framework 4.5.2+ and .Net 5+, using NUnit, xUnit, REST, Kafka/RabbitMQ, Git, and Linux. You will build Citi’s next-generation Equities technology platform for execution, clearing, and margin processes.

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.

You will work with Java and SpringBoot microservices on Linux and OpenShift, building APIs and using build tools like Gradle, CI/CD, Git, and BitBucket/GitHub. As part of the Technology Application Strategy team, you will design and deploy cutting-edge developer tooling and productivity solutions for Citi’s global developer community.

Develop dashboards and reports using Power BI, SQL, NoSQL (MongoDB), Linux/Unix, modern cloud tools, and languages like C#, Python, or Java. You’ll join a hyper-scaling fintech start-up building a market-altering product.

Java (JDK 11+), multithreading, SQL/NoSQL databases (Oracle, MySQL, PostgreSQL, MongoDB, Cassandra), message queuing (Kafka, Tibco, Solace), Linux, JVM, and TDD. This tech lead role builds high-performance FX risk calculation systems for Citi’s Markets technology team, which supports global trading and risk management.