Europython

Our Quantitative Developers are the enablers of our success. They work side-by-side with our researchers to realise their ideas in global financial markets. They work at the bleeding-edge with immense compute power at their fingertips to achieve our aim: predicting the future. The core tech stack is C# and Python, productionised in our own datacentres. Areas of focus Trading systems - reliable and performant systems able to trade 24/6 for our customers, with real money at stake Modelling - building core capabilities and assisting quant researchers in our cutting edge prediction capabilities Simulation - back-testing frameworks for validating the strategies our researchers produce and for assessing their ongoing performance Research tooling - front-end UX and workflow for our quant researchers Performance and scalability - optimising our trading and research systems to unlock new capabilities

Overview We are looking for exceptional machine learning engineers to work alongside our quantitative researchers on cutting-edge machine learning problems. As a member of the Core Technical Machine Learning team, you will be engaged in a mixture of individual and collaborative work to tackle some of the toughest research questions. In this role, you will use a combination of off-the-shelf tools and custom solutions written from scratch to drive the latest advances in quantitative research. Past Projects Implementing ideas from a recently published research paper Writing custom libraries for efficiently training on petabytes of data Reducing model training times by hand optimising machine learning operations Profiling custom ML architectures to identify performance bottlenecks Evaluating the latest hardware and software in the machine learning ecosystem

Engineering underpins our continued growth and success, and we are committed to recruiting and developing the world's best Engineers. Our teams develop and build tooling for a petabyte-scale compute farm; your code will exist at the cutting-edge underpinned by near infinite compute power. Most of our systems are written in C# or Python, but we also have specialist teams using C++, Java and F#. We utilise modern web, distributed and big data technologies, which means we have a broad range of software engineering challenges for the right person. Key responsibilities of the role include: Contributing to the evolution and successful operation of a world-class trading system Designing and building solutions that drive value for our petabyte-scale data platform Continuously exploring and developing solutions to improve data and compute throughput at scale Demonstrating software engineering best practices

We are looking for exceptional engineers to help us build out a mature ML research and deploy pipeline as part of our ML Workflows team. This is an exciting role. You will develop greenfield solutions to meet highly complex ML interdependency requirements. Where off-the-shelf tools fall short, you'll build custom solutions to define best practice across quantitative research. Future projects include: Implementing best practice feature and model stores Properly versioning features, data and models Improving inference compute utilisation via model serving CI/CD for ML Reliably fitting models with complex job dependency graphs Robustness in production, including validation and monitoring