2026 - Internship, Quantitative Developer - Low-Latency and Market Microstructure

Programme duration: from 5 to 6 months, starting in 2026.   

Who qualifies: Final year students completing a Bachelor's, Master's.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.  

Over the years, QRT has invested in a global research and execution platform which has been deployed to cover all geographies and asset classes. This platform covers a broad spectrum from high to low frequency trading systems. We thrive at the intersection of cutting-edge technology, smart automation, and scalable processes, enabling us to move fast, think big, and deliver at scale.   

We are committed to identifying and developing exceptional talent, and are inviting a new cohort of outstanding individuals to join us in the year ahead. Our internship offers a stimulating, intellectually rigorous, and high-performance environment, where collaboration is key to success. You will work alongside and be mentored by industry-leading professionals, gaining invaluable experience and positioning yourself for the opportunity to secure a full-time graduate role upon successful completion of the program. 

Your future role at QRT  

As a Quantitative Developer for Low-Latency and Market Microstructure, you will help optimize exchange connectivity and interaction for our high-frequency trading strategies. You will analyse network and exchange protocols, automate performance metrics, and lead experiments to improve our trading operations, with a focus on latency-sensitive exchanges.

• Network & Protocol Analysis: Analyse network and exchange protocol captures to identify inefficiencies and improve communication performance.
• Execution Optimization: Reverse-engineer trading systems and design and conduct experiments to improve fill rates.
• Data Analysis: Effectively work with large and robust datasets to identify and resolve inefficiencies in internal execution systems and exchange communication.

Your present skillset  

• Strong core computer science foundations, including algorithms, data structures, parallel programming, and object-oriented programming (OOP). 
• Genuine interest in software engineering, data analysis and/or low-level systems and network engineering.
• Strong skills in Python and time-series analysis.
• Understanding of network protocols such as TCP/IP and Ethernet.
• Excellent communication and analytical skills – you will interact directly with Traders and Researchers . 
• Drive for rapid autonomy and the ability to work in a fast-paced, high-performance setting. 
• Rigorous and structured approach to problem-solving. 

Preferred qualifications (a plus): 

• Familiarity with market microstructure and low-latency trading.
• Networking and GNU/Linux knowledge.
• Interest in financial markets and/or algorithmic trading. 

Interview Process 

•  Application - Submit your application online. We review applications on a rolling basis, so we recommend applying early to maximize your chances. 

• Technical Assessment - Selected candidates will be invited to complete a coding challenge designed to evaluate core technical and problem-solving skills. 

• Interviews - Shortlisted applicants will proceed to interviews, conducted either on-site or via Microsoft Teams. These will assess both your technical expertise and your alignment with our culture and values. 

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.