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, New York, Singapore, 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.
XTY Labs, a division of XTX Markets established in 2024, stands at the intersection of finance and cutting-edge machine learning research. The lab is designed to be a home for those eager to pioneer the future of algorithmic trading, with a strategic focus on developing and applying novel machine learning techniques to financial data. Situated in Hudson Yards, New York City, XTY Labs offers a state-of-the-art, "academia-like" workspace designed to inspire creativity and innovation. Led by Research Director Dr. Atlas Wang, researchers will have the opportunity to explore new ideas and transform their advanced machine learning research into real-world financial solutions, backed by XTX Markets' expansive research cluster, rich datasets, and advanced technological infrastructure. Emphasizing practical application, XTY Labs' mission is to swiftly integrate successful models into the market, directly enhancing XTX's trading strategies and operations. This direct pipeline from research to implementation establishes XTY Labs as a premier destination for those looking to make a significant impact in the financial sector through original machine learning research.
The XTY AI Research Internship
Please note that we are now only accepting applications from candidates who are available starting from January 2027 or later.
This 12–14-week research-focused internship, is designed for highly motivated students in the middle years of their advanced degrees, who are eager to push the boundaries of high-risk, high-reward AI research and rapidly integrate cutting-edge ideas into our advanced strategies. Top performing interns will be actively considered for full-time research roles in either our NYC or London teams.
Why Join?
- Work at the Frontier of Fundamental AI Research: Explore and innovate at the forefront of machine learning, optimization, generative AI, foundation models, distributed training, and other cutting-edge areas, driving direct business impact.
- Fast-Paced Innovation: A unique opportunity to test, iterate, and refine cutting-edge concepts at industry speed, all taking place in weeks if not days.
- Mentorship & Collaboration: Each intern will be paired with at least one full-time researcher as a mentor and will also work closely with the research director for guidance and collaboration.
- Exposure to Real-World Quantitative AI: Experience firsthand how advanced AI techniques shape algorithmic trading in one of the world's most technologically sophisticated firms.
This is an exclusive opportunity for students who excel in research-driven environments and are eager to make a meaningful impact in a field still rich with untapped potential in the GenAI era. Our environment is designed for innovation with a flat organizational structure, a friendly and collaborative culture, and an absence of red tape, allowing you to focus on advancing the field of machine learning in finance. You will work from our NY office at least 4 days per week.
Responsibilities
- Engage in pioneering research to devise original machine learning algorithms, with the autonomy to investigate and apply novel methods.
- Utilize a broad knowledge base across deep learning, natural language processing, time series analysis, control and optimization, reinforcement learning, among others.
- Architect, build, and refine models, agents, and software prototypes with a focus on robustness and generality.
- Clearly communicate research progress and findings, ensuring efficient internal knowledge transfer both verbally and in writing.
- Foster teamwork and collaborate with XTX Markets' quantitative research team, contributing to a collective effort of fewer than twenty experienced researchers.
The program offers an unparalleled opportunity to work within a rich computational environment, equipped with an impressive array of resources. Interns will immerse themselves in a culture that promotes collaboration, innovation, and a flat hierarchy. The program is designed to bring together a wide range of backgrounds and interests, not only those who are already set on a career in finance.
Essential Attributes
- Pursuing an advanced degree, ideally Ph.D., in computer science, electrical engineering, mathematics, or a related quantitative field, with at least one year remaining before your expected graduation date.
- Strong evidence of ability to conduct original research. That shall include a proven publication record in leading machine learning and AI venues (we do not count publication numbers)
- Demonstrated practical experience and deep understanding of modern deep learning architectures, in particular transformers and its variants.
- Solid knowledge in fundamental data science, optimization, and statistics
- Solid programming skills (language does not matter; Python is fine)
- No prior experience in finance is needed.
Desirable Attributes
- Proven expertise in developing and working with foundational models, including but not limited to large language models and multi-modal frameworks.
- A background in managing and analyzing large, unstructured, and noisy datasets.
- Hands-on knowledge of time series forecasting.
Compensation
The base salary for the AI Research Internship role will be $35,000 per month. You will enjoy similar benefits to those of our US permanent employees as appropriate and receive a generous sign-on bonus to be used for covering accommodation costs.
Interview Format
We plan to keep our internship cohort small, with a highly selective application process. Our interview process seeks to gain signal in the following topics:
- Modern machine learning techniques, especially deep learning
- Classical machine learning techniques
- General mathematics (linear algebra, analysis, probability etc.)
- Hands-on programming and data engineering
We seek to get a broad signal in our process. Successful candidates are those who are strong in all areas and exceed expectations in at least one. Your interview process will follow a four-stage format:
- An introductory conversation with the recruitment team.
- A practical take-home exercise, where you are provided with a dataset to construct and develop an AI model comprehensively from start to finish.
- A discussion with the Research Director to delve into your research history, knowledge in deep learning/machine learning, compatibility with XTY's goals, and to gauge your innovative thought processes.
- A final 1-hour interview with either an XTX Quantitative Researcher or XTY full-time Researcher.