Software Developer - Research Technology

XTX Markets is a leading algorithmic trading firm which uses state-of-the-art machine learning technology to produce price forecasts for over 50,000 financial instruments across equities, fixed income, currencies, commodities and crypto. It uses those forecasts to trade on exchanges and alternative trading venues, and to offer differentiated liquidity directly to clients worldwide. The firm trades over $250bn a day across 35 countries and has over 250 employees based in London, Singapore, New York, Paris, Bristol, Mumbai, Yerevan and Kajaani.

We leverage the talent of the people who work here, modern computational techniques and state-of-the-art research infrastructure to analyse large data sets across markets quickly and efficiently, to maximize the effectiveness of our proprietary trading algorithms. We are actively seeking new methods and ideas. The models that drive our trading strategies have evolved considerably over the last 10 years, from econometric methods that gave our company its name, to trees, to neural networks, to modern deep learning architectures.

XTX Markets has an unrivalled level of computational resources in the trading industry, with a growing research cluster currently containing over 25,000 GPUs with 650 petabytes of usable storage. Teams across the firm include world-class researchers, developers and technologists with backgrounds in pure math, programming, physics, computer science and machine learning. The firm is also constructing a large-scale data centre in Finland to future-proof its significant computational capabilities.

At XTX Markets technology is our business and we are a diverse organization which attracts outstanding talent from across all industry backgrounds. We are focused on teamwork and our people collaborate on all aspects of the business, working openly and with respect for each other, our clients and the market. Our culture is non-hierarchical and one where everyone is valued. We strive for excellence in everything we do.

XTX is a research-driven organisation, built and led by passionate mathematicians and computer scientists. The Research Technology team lies at the heart of the company – the CPU and GPU clusters are understandably regarded as some of the firm’s core assets, and driving their development forward is a primary focus of XTX. The research performed on the cluster is fundamental to the firm’s success.

What we are doing:

• The cluster spans multiple data-centres and accommodates multiple tenants, providing CPU and GPU for executing tasks, running services, housing LLMs etc. We are actively expanding the features and UX that we provide to quants and other teams within XTX.
• We have built and open-sourced our own exa-scale filesystem, designed to handle billions of directories, a trillion files and a million clients spanning multiple datacentres, whilst offering complete resiliency. You can read more about it here. Current projects include proving full NFS access, optimising storage services, io feature expansion (e.g. greater POSIX compatibility, creating an iSCSI target), bandwidth optimisation etc.
• We have several low-level technical projects including file system optimisation, storage performance, file compression, network segregation, as well as network, GPU and system performance management.
• Higher level projects include service failover, system and configuration deployment, hardware failure management.

• →A solid grounding in academic CS fundamentals (algorithms and data structures).
• →Proficient in at least one statically typed language; development with be using Golang and Rust though experience in these is not a pre-requisite. Scripting is mainly in Python.
• →Approximately 5-10 years’ experience designing and building large-scale distributed systems; with the ability to develop highly scalable solutions to problems.
• →Strong problem solving and analytical skills.
• →Familiarity with the Linux operating system; able to engage in diagnosing issues, specifically those associated with performance and scalability.
• →Ability to multi-task, working on multiple projects at once and prioritise appropriately across them.
• →Be highly self-motivated and able to work independently without supervision.
• →Understanding of one or more machine learning frameworks and compute offload devices, like GPUs, is an advantage.