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

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.

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

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.

Lovable★4.0 (43)· London

Uses Go, Rust, TypeScript; AWS, Azure, Google Cloud, Cloudflare; Kubernetes, Terraform, Temporal, OTEL, CI/CD; PostgreSQL, ClickHouse, Firestore, Spanner, BigQuery. Builds the platform for Lovable Enterprise enabling secure, cloud-agnostic deployment, defining architecture for sandboxing, networking, encryption, identity, and mentoring engineers.

RELX Group★3.8 (133)· London

You will work with Java/J2EE, JavaScript, JSP, C/C++, HTML, XML, SQL, Windows, UNIX, and .Net. The team supports products for education electronic health records that introduce students to digital charting and prepare them for clinical documentation.

Elsevier★3.8 (769)· London

Work with Java/J2EE, JavaScript, JSP, C/C++, HTML, XML, SQL, Windows, UNIX, .Net, and various data storage subsystems. You'll develop complex software solutions supporting educational electronic health record products that prepare students for digital charting in clinical environments.

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.

You will use C++ and Python to build and maintain core vanilla pricing models for commodities on the Commodities Risk & Pricing team. You will own the risk and pricing libraries used firm-wide, partnering directly with traders and structurers.

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.

Advanced Python (object-oriented design, performance optimisation, testing), SQL, and exposure to distributed systems, APIs, and cloud environments. You will design, build, and maintain Python-based pricing and analytics libraries for front-office teams, implementing models for risk, valuation, and P&L analysis. Quanteam provides high-impact consulting in quantitative finance, risk, data, and technology.

Quantitative Developer role involving C#, C++, or Python and an in-house big data language. You will design, build, and validate pricing models, libraries, calculators, and risk algorithms for a trade surveillance product that detects market manipulation using sophisticated modelling.

You will work with Python, C++, HPC, and distributed systems to build tools for quant research, signal generation, and large-scale data pipelines. The team develops the infrastructure powering trading signal research, letting researchers and traders test and scale strategies across global markets.

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.

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’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.