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2027 – Graduate or Internship, Infrastructure Engineer

Qube Research & TechnologiesLondon, ParisPosted 29 Sept 2026

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EMEA 2027 – Graduate or Internship, Infrastructure Engineer Location: London, Paris Programme duration: 3–6-month internship, 12-month industrial placement or graduate position Who qualifies: Penultimate or final-year students completing a bachelor’s or master’s degree Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager operating across liquid asset classes and markets worldwide.

Our approach to investing is scientific: we bring together data, research, technology and trading expertise to develop and run systematic strategies. Technology is central to how QRT works. Over the years, we have built a global research and execution platform spanning geographies, asset classes and trading horizons, from ultra-low-latency systems to large-scale research, analytics, and risk infrastructure. We invest heavily in engineering, automation, and scalable systems because better technology allows us to test ideas faster, operate more reliably, and tackle harder problems.

Our internships are designed to give students meaningful experience of that work. You’ll join a team, contribute to real projects, and learn from engineers, researchers, and traders working on live problems. The environment is technical and collaborative, with plenty of scope to ask questions, explore different approaches, and take ownership. Strong performance during the internship may lead to consideration for a full-time graduate role.

Your future role at QRT As part of QRT’s Infrastructure group, you’ll help build and operate the systems behind our research, trading and business activities. The work spans hardware, operating systems, compute, storage, networking and platform engineering, with a common focus on performance, reliability and automation. Throughout the recruitment process, we’ll consider your skills and interests alongside the problems our teams are working on.

Depending on the strongest fit, your internship may focus on one of the following areas: Infrastructure The Infrastructure team looks after the on-premise hardware and operating systems behind our production trading environment. The work goes well beyond keeping systems running: engineers measure and optimise hardware performance, investigate Linux internals and tune systems where small changes can make a meaningful difference.

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You’ll develop a detailed understanding of how hardware and software interact and how to make production systems faster, more stable and more predictable. Research Infrastructure Research Infrastructure builds and operates the high-performance compute, networking and storage systems behind QRT’s research. These systems support large-scale data processing, advanced analytics and machine learning and AI workloads using technologies such as PyTorch.

The team works closely with researchers to understand what their workloads need and design infrastructure that can meet those demands efficiently. The aim is simple: give researchers reliable, scalable compute so they can spend more time on research and less time thinking about the infrastructure underneath it. HPC Storage The HPC Storage team builds and operates the high-performance storage infrastructure behind large-scale research and computing workloads across QRT.

The problems involve moving and serving large volumes of data reliably, securely and quickly enough to support demanding simulations and analyses. You’ll work with enterprise-scale storage technologies and collaborate with engineers, researchers and technology vendors. It’s an opportunity to understand storage at scale, from the underlying architecture and performance characteristics to the way researchers and compute systems interact with it.

Network Operations Network Operations is responsible for the availability, reliability and security of QRT’s global network, connecting the systems behind our research and trading activities. The team investigates incidents, develops observability tooling and builds automation to make operating the network more reliable and efficient. Alongside day-to-day operations, the team works on the infrastructure needed for high-performance compute and low-latency trading.

This means understanding how networks behave in practice, finding the source of difficult problems and looking for ways to make systems simpler to operate and easier to observe. DevOps (London & Paris) Platform Engineering builds and automates the infrastructure, tools and workflows behind QRT’s research and trading platforms. Working across cloud and on-premise environments, the team brings together DevOps, cloud, networking, security, infrastructure and software engineering.

You’ll work on the systems that allow researchers and developers to build, deploy and operate technology efficiently at scale. That could mean improving deployment workflows, automating infrastructure or finding better ways to make complex systems reliable and repeatable. SRE (London & Paris) Site Reliability Engineering sits at the intersection of software engineering, quantitative research and trading. Working closely with researchers and traders, the team builds reliable, high-performance systems and develops tooling and automation for deployment, monitoring, operations and incident response.

The work combines software engineering with an interest in how systems behave in production. You’ll investigate technical problems, improve observability and help design systems that remain resilient as they scale, while developing an understanding of the quantitative workflows they support. Your current skillset Eligibility – Penultimate or final-year students pursuing a Bachelor’s, Master’s in a STEM discipline, such as Computer Science, Information Technology, Networks or a related subject, on track for a 2:1 or above.

Interest in technology – We’re interested in what you’ve explored and built, whether through hobbies, personal projects, academic work or open-source contributions. Technical skills – You don’t need experience with everything below. D

Source listing: greenhouse_quberesearchandtechnologies

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