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.

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.

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.

Develop and enhance ultra-low-latency XVA pricing services for linear products using C++. The front-office quantitative technology team focuses on sub-5ms pricing and XVA sensitivity calculations (CS01, strike). No team size or leadership scope is specified.

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 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.

You will work with C++17+, kernel tuning, network optimisation, and low-level profiling on Linux to build latency-critical HFT systems. The team designs end-to-end architectures for a tech-driven quant and systematic hedge fund, collaborating with FPGA, hardware, and infrastructure engineers.

You will work with C++17+ in a low-latency HFT environment, performing kernel-level tuning, network optimization, and systems programming. The team builds and operates ultra-low-latency trading systems for a global quant hedge fund, collaborating with FPGA and hardware engineers on end-to-end architectures where every nanosecond counts.

You will use modern C++ (C++17+) and Python to develop quantitative models for derivatives in the Commodities Quant team of a top hedge fund. Work includes building risk metrics, forward curves, volatility surfaces, timeseries data handling, and VaR models for portfolio managers.

Design, build, and optimize large-scale HPC/AI infrastructure using GPU optimization (CUDA, NCCL, GPUDirect RDMA, NVLink). You'll work with triple-digit petabyte-scale storage and massive CPU/GPU clusters, using Python, C/C++, and Linux in globally distributed data centers. This role covers HPC cluster design, performance tuning, and automation for thousands of nodes.

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.

You will build and optimise low-latency trading system components in modern C++ for a fully automated electronic trading platform. You will design real-time infrastructure for market data ingestion, order execution, and exchange connectivity, working with quantitative researchers and traders.