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Location: London 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 QRT’s 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. Your future role within QRT This team is integral to the firm’s success. We are seeking a technically skilled Data Support Engineer to support quantitative researchers and traders in navigating and using extensive datasets. You will support all data users, contribute to documentation, and ensure data quality. Provide first-line support to researchers and traders for data access ad usage Collaborate with data engineers to resolve data issues Onboard new hires and train them on using data tools and processes efficiently Manage JIRA workflows, track support requests, and ensure timely resolution of data issues Contribute to data documentation Contribute to extending data coverage (live collection and backfills) Your present skillset A Bachelor’s degree in Data Science, Computer Science, Finance, or a related field Experience in data support, IT helpdesk, or technical support, ideally within finance Strong command of Python and data libraries Proficiency with data systems, pipelines, and APIs Experience with JIRA or similar project management tools Strong problem-solving skills, communication abilities, and attention to detail 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.

Location: Hong Kong 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. Your future role within QRT The successful candidate will join the global infrastructure team at QRT. This team is responsible for our rapidly growing Linux estate, including our global trading infrastructure and low-latency trading platform. The candidate will work closely with application and support teams to ensure we deliver a high performance, secure, and scalable platform for the business. The role has a strong focus on automation, and you will be responsible for providing the tools, processes and standards we use to manage and expand our Linux environment. This role is based in Hong Kong and will be the first platform engineering hire in APAC. You will be joining a well-established local infrastructure department and working alongside experienced colleagues in region. You will be the local representative of the global platform engineering function, within infrastructure and to APAC stakeholders more widely. This is a senior individual contributor role in which you will be trusted to work independently. You will be working on global solutions and contributing to the architecture and standards that underpin them, while ensuring regional solutions align with that global direction. In addition, as the regional platform engineering representative you will: Act as the primary point of contact in APAC for platform engineering, providing in-region engineering coverage during local market hours (production operations and incident response sit with a dedicated operations team). Gather, consolidate and advocate for regional requirements, ensuring APAC needs are properly represented in the global team's roadmap and design decisions. Ensure global standards, tooling and processes are consistently applied across the region's Linux estate, and identify where regional divergence needs to be addressed or legitimately accommodated. Lead or contribute to engineering projects with a significant APAC component. Partner closely with the local infrastructure department and regional stakeholders, building the relationships that help ensure engineering initiatives work effectively in region. Your present skillset: In depth knowledge of Linux (preferably RedHat distributions), with experience in building and administering trading platforms. Extensive experience with architecture and long-term evolution of automation / configuration management systems. Ansible experience preferred. Experience with monitoring and observability tools such as Splunk, Prometheus, Grafana. Experience with build/release management systems. Solid programming skills in Python and Bash. C/C++ is a bonus. Detailed understanding of server network stack, network protocols (e.g. TCP, UDP, IGMP), LAN and WAN technologies. Experience of performance analysis and tuning. Experience working in a collaborative development environment using source control. Strong problem solving and analytical skills. Experience driving adoption of engineering standards across teams; experience contributing to or defining those standards is an advantage. Good team player with a willingness to help others. Strong interpersonal and communication skills. 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.

Location: London 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 QRT’s 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. As QRT’s infrastructure estate grows, maintaining accurate data on its resources, ownership and performance is increasingly important. In this hands-on role, you will build and operate the data foundations underpinning our infrastructure inventory and observability capabilities. The focus extends beyond dashboard design to creating an accurate, consistent and reliable view of the platform, its ownership and its behaviour. Your future role within QRT: Design and build data models for infrastructure and operational data, defining canonical representations for resources, ownership, capacity and utilisation. Integrate inventory, configuration, security and observability data from multiple systems into a coherent, queryable view. Keep key counts and metrics consistent across different consumers, and make data lineage, ownership and limitations explicit. Design data structures that are fast to query and easy to reason about at the scale of QRT’s estate. Automate data processing, validation and delivery, and build the tooling to detect data-quality, freshness and performance issues before consumers do. Investigate and resolve data-quality, freshness and performance issues, solving root causes rather than symptoms. Collaborate closely with infrastructure, security, engineering and observability teams to onboard new sources and improve the accuracy of the platform view. Take ownership of systems end-to-end, and adapt the platform as scale, requirements and underlying technologies change. Your present skillset: Experience building and operating production-grade data platforms, analytical data models, or large-scale data-processing applications. Strong SQL and dimensional or analytical data modelling experience, including the design of schemas that are maintainable, performant and easy for consumers to reason about. Strong Python software engineering experience, including the design of maintainable, tested production applications and scalable ETL/ELT pipelines. Demonstrated rigour around data correctness: establishing provenance, reconciling conflicting or incomplete sources, and reasoning carefully about identity, ownership and source of truth. Solid working understanding of infrastructure and observability concepts, and comfort working across data, infrastructure and observability domains. Experience operating business-critical pipelines and diagnosing data, performance and reliability issues in production. Familiarity with knowledge graphs, ontologies and taxonomies, and their application to modelling heterogeneous operational data. A strong bias towards automating repetitive work, and pragmatism in balancing correctness, performance and delivery. Excellent problem-solving and communication skills, and the ability to own outcomes across research, engineering and infrastructure teams. Preferred: A background in data science, statistics or applied machine learning, particularly applied to incomplete, noisy or inconsistent data, or to inferring missing information and identifying unusual behaviour. Experience with SQL-based analytical platforms, dbt, object storage and data catalogues. Experience with infrastructure inventory or CMDB data, ownership and capacity/utilisation modelling. Experience with metrics, logs and vulnerability data, and with observability tooling. Experience with Superset or comparable BI and data-exploration tools. Experience with Linux, containers and GitLab CI/CD. Experience with AWS services and cloud SDKs. 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.

Location: Hong Kong 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. You will join the Cloud Infrastructure team in Hong Kong. As QRT continues to expand across APAC, the team is scaling to support a growing book of work across trading and research workloads, from traditional strategies to digital assets. We work shoulder-to-shoulder with engineers, researchers, and trading desks to deliver secure, reliable, and scalable infrastructure with a sharp focus on business outcomes. Your Future Role within QRT Provide end-to-end infrastructure ownership across the full lifecycle: architect, implement, run, and troubleshoot cloud and on-prem environments. Design and execute deployment strategies on AWS, while extending support to on-premises container platforms Partner directly with trading desks, developers, and researchers to translate business requirements into robust technical solutions, delivering quickly without unnecessary bureaucracy Drive CI/CD adoption, automation, and infrastructure-as-code practices to streamline software delivery across both cloud and on-prem estates. Engineer and maintain network, security, and monitoring solutions that ensure the availability, performance, and reliability of production trading systems. Support containerised workloads (Docker, Kubernetes), including cluster management and performance tuning, on both AWS and emerging on-prem platforms. Evaluate and introduce new tooling to improve DevOps efficiency, remaining pragmatic and outcome-focused. Act as a business-oriented liaison between engineering and business teams, facilitating clear communication, managing demanding stakeholders, and ensuring infrastructure decisions align with commercial goals. Thrive in ambiguous environments where roadmaps are driven by business need; you will help define the architecture even when specs are still evolving. Your Present Skillset 3 to 8 years of hands-on infrastructure or cloud engineering experience. Extensive experience with AWS services and infrastructure (e.g., EC2, S3, VPC, IAM, networking, security). Hands-on experience with containerisation and orchestration (Docker, Kubernetes), including on-premises cluster management. Strong grasp of CI/CD principles and tooling (Jenkins, GitLab CI, or similar). Proficiency in Python or Bash for automation. Experience with infrastructure-as-code tools (Terraform, CloudFormation, or AWS CDK). Solid understanding of Linux, networking, and performance optimisation. Familiarity with time synchronisation concepts and protocols (NTP / PTP). A proven ability to work autonomously: given a problem statement, you self-source what you need and deliver a production-grade solution without hand-holding. Excellent communication and collaboration skills; comfortable working alongside highly competent peers and demanding business stakeholders. A team-player mindset with a bias for action and a track record of delivering tangible business outcomes. 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.

Location: London QRT is a global quantitative and systematic investment manager, operating across all liquid asset classes. We are a data- and technology-driven organization applying scientific methods to investing. Our collaborative culture and focus on innovation enable us to solve complex challenges and deliver high-quality returns for our investors. The AI Security function is engineering the controls that allow the firm to adopt frontier AI quickly and safely. The function works across engineering, infrastructure, cloud and security to build controls into the platforms, inference gateways and developer tooling already used across the firm. Your future role within QRT We are seeking an exceptional Staff Security Engineer to join our AI Security function. The role is expected to involve the following activities: •  Design and implement security controls in the inference gateways, platforms and developer tooling used across the firm, delivered as code and configuration. •  Embed controls in the systems that engineering teams already work in, so that the secure option is the default. • Define the standards and patterns other teams adopt when building with AI. • Define who an internal agent acts as, what it is permitted to reach and how those decisions are enforced. • Build telemetry that records what ran, on whose behalf and against what. • Establish how agent and automation activity is proven after the fact for audit and investigation. • Secure developer harnesses, plugins, and the dependency and model provenance they rely on. • Own secrets handling and vulnerability management across the AI tooling the firm depends on. • Set provenance and integrity requirements for models and components introduced into the firm. • Threat model live systems across platform and gateway security, agent identity and permissioning, and the AI supply chain. • Deliver the remediation resulting from threat modelling directly. • Identify gaps in control coverage and prioritise remediation against risk and delivery constraints. • Take and document control decisions in areas where no established answer exists. • Set and own the technical direction for the function’s core areas and help define how the function works. • Drive the adoption of secure defaults and governed identities and gateways with a reliable audit trail. Your present skillset •  Experience with LLM platforms, inference gateways or agent frameworks. • Eight or more years of experience in security engineering, software engineering, platform engineering or a closely related technical discipline. • A strong academic record in computer science or software engineering. • The software engineering ability to build and ship controls in production systems, not only review them. • Depth in at least one of application security, platform and cloud security, or security architecture, with working breadth across the others. • Hands-on experience securing cloud platforms and CI/CD pipelines. • The judgment to work in an area with no established practice and make control decisions using incomplete information. • Fluent day-to-day use of coding agents. Desirable to have experience or a willingness to learn in the following areas • Working in a regulated or high-security environment. • Detection engineering or incident response. • Defining security practice in a function or capability that did not previously exist. 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.

Location: London QRT is a global quantitative and systematic investment manager, operating across all liquid asset classes. We are a data- and technology-driven organization applying scientific methods to investing. Our collaborative culture and focus on innovation enable us to solve complex challenges and deliver high-quality returns for our investors. The newly formed Reference Data Technology Team is building a new reference data system. The team works with stakeholders across Trading, Operations, Compliance and Research to translate business and regulatory requirements into data models, datasets and data quality controls. Your future role within QRT We are seeking an exceptional Reference Data Business Analyst to join our Reference Data Technology Team. The role is expected to involve the following activities: Translate business and regulatory requirements into data entity models and datasets for the new reference data system. Work closely with the Data/Platform Architect to ensure business requirements map cleanly onto the technical model. Gather and validate requirements directly with domain stakeholders across Trading, Compliance and Research. Partner with Trading, Operations and Compliance teams to build automated data quality rules and checks, exception-management workflows and metrics. Provide day-to-day support to business, compliance and technology teams as a subject matter expert on data queries and system behaviour. Apply expert knowledge of equity reference data, related events, and the lifecycle and processing of corporate actions. Support the initial delivery focused on Equities and ETFs and its direct impact on the trading business. Produce data dictionaries, entity relationship diagrams and requirements specifications. Your present skillset Experience producing entity and data models for reference or master data platforms in financial services. Deep working knowledge of ETF reference data, including composition and basket data, creation and redemption mechanics, and identifiers. Hands-on knowledge of ETF corporate actions processing, including dividends, splits, mergers and delistings. Understanding of corporate actions lifecycle stages, timing and effective-date handling, and the downstream impact of processing errors. Experience defining corporate actions data quality rules, including the detection of missed or conflicting action records and effective-date validation. Strong requirements-gathering skills across multiple stakeholder groups, including Trading, Compliance and Operations. Working knowledge of data quality concepts, including completeness, accuracy, timeliness and referential integrity. Ability to translate regulatory and business rules into structured, testable data rules. Comfortable working directly with technical architects to map business requirements onto a reference data model. Strong written documentation skills, including data dictionaries, entity relationship diagrams and requirements specifications. Strong database and SQL skills for data interrogation and analysis. Desirable to have experience or a willingness to learn in the following areas Client and account reference data, including legal entity structures, KYC, account hierarchies and LEIs. Master data management concepts, including golden source, survivorship and entity resolution. Scoping an MVP and maintaining a firm line on deferred scope. Data lineage, metadata cataloguing and associated tooling. Data modelling tools, including entity relationship diagramming and data catalogue tools. UK and EU financial services regulatory frameworks relevant to reference data, including the LEI regime and KYC/CDD requirements. Python experience and knowledge. 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.

Location: Paris, London Programme duration: from 5 to 6 months, starting in 2027. Who qualifies: Penultimate or final year students completing a Bachelor's, Master's. 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 and data are 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 data 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 work alongside engineers, researchers and traders on problems that matter to our research and trading activities. The environment is technical and collaborative, with plenty of scope to ask questions, test ideas and take ownership Your future role at QRT As part of QRT’s data teams, you’ll work on the systems and datasets behind quantitative research and trading. You’ll collaborate closely with traders, researchers and engineers, tackling problems across data acquisition, engineering and platform design. 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: Quantitative Data Analyst – Source and evaluate new datasets based on priorities from our trading desks. You’ll explore how new data can support research, manage sourcing projects from acquisition through to design, and work with Data Engineers to bring useful datasets into production at scale. Data Engineer – Work with large datasets across QRT’s research and trading platforms. You’ll design and implement data stores and APIs, monitor data processes and build production-ready datasets that researchers and traders can use effectively. Data Platform Engineer – Build and maintain the infrastructure used to ingest, process and serve data across our research environment. You’ll work on real-time and batch workflows, with a focus on reliability, latency and efficiently handling growing volumes of complex data. Your present skillset Computer science foundations – A good grounding in areas such as algorithms, data structures, parallel programming and object-oriented programming. Programming – Experience with Python and an interest in using software to solve data or infrastructure problems. Engineering interests – An interest in software engineering, infrastructure or data engineering, particularly where performance and reliability matter. Systems – Curious about high-performance, real-time systems and interested in developing a deeper understanding of how they support trading. Problem solving – A rigorous, structured approach to analysing unfamiliar problems and working towards practical solutions. Communication – Able to communicate clearly and collaborate directly with researchers, traders and engineers. Approach – Self-motivated and keen to develop autonomy as you learn. Preferred qualifications (a plus): Knowledge of SQL or NoSQL databases. Experience with front-end development. An interest in financial markets and/or algorithmic trading. Interviewing Application – Submit your application online. We review applications on a rolling basis. Technical Assessment – Selected candidates will complete a coding challenge focused on core programming and problem-solving skills. Interviews – Shortlisted candidates will take part in interviews, either on-site or via Microsoft Teams. We’ll explore your technical foundations, how you approach unfamiliar problems and how you work with others. 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.

Location: Aarhus, Budapest, Dubai, London, Paris, Zurich Programmes offered: Final-year internship, penultimate-year internship, some permanent opportunities Programme duration: 4–6 months, starting in 2027 Locations: Aarhus, Budapest, Dubai, Geneva, London, Paris, Zurich Who qualifies: Penultimate or final-year students completing a bachelor’s, master’s or PhD 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. Research is central to how QRT invests. Over the years, we have built a global research and execution platform spanning geographies, asset classes and trading horizons, from high to low frequency. This gives our researchers access to large and diverse datasets, sophisticated research tools and the infrastructure needed to turn research ideas into live trading strategies. Our internships are designed to give students meaningful experience of that process. You’ll join a systematic team, work on real research or trading problems and learn from experienced researchers and traders. The environment is rigorous and collaborative: ideas are tested against data, assumptions are challenged and good questions matter as much as quick answers. Your future role at QRT Throughout the recruitment process, we’ll consider your skills and interests alongside the problems our teams are working on, with the aim of finding the strongest fit. As a Quantitative Research Intern, you could contribute in one of two complementary areas within one of QRT’s systematic teams, spanning high, mid and low frequencies: Research Your focus will be on developing predictive signals from large and varied datasets. You’ll explore the data for patterns and form hypotheses about what might be driving them. From there, research is iterative: you’ll design tests, question the results, adjust your approach and test again. Working with other researchers, you’ll learn to distinguish promising signals from noise. In doing so, you’ll experience the full research process, from an initial observation to something that can be used in live trading. Trading You’ll contribute to the live deployment of QRT’s research by working directly with our systematic trading platform. You’ll monitor how signals behave in production, track performance, improve execution efficiency and help identify and manage potential risks. Working closely with senior Researchers and Traders you’ll investigate how strategies behave in production and look for ways to make them more robust and scalable. You’ll use quantitative analysis and programming to understand what is happening in live systems and determine where improvements can be made. Across both areas, how you approach a problem matter. We’re looking for interns who are curious, creative and collaborative. You should be comfortable exploring ideas, asking questions and learning as you go. Your present skillset Academic background – Pursuing an advanced degree in a quantitative field such as Data Science, Statistics, Mathematics, Physics or Engineering. Quantitative foundations – Strong analytical skills and an interest in using mathematics, statistics and computation to understand complex problems. Programming – Coding experience in at least one leading programming language, including Python, C++ or C#. Research interests – Knowledge of statistics, machine learning, NLP or AI techniques is useful but not essential. Data – Experience exploring large datasets across multiple time horizons is a plus. Problem solving – Able to work through complex problems rigorously while maintaining strong attention to detail. Independence and collaboration – Comfortable working autonomously while exchanging ideas and working closely with colleagues from different disciplines and backgrounds. Communication – Able to explain your reasoning and communicate technical ideas clearly. Languages – Fluent in English; additional languages are a plus. Interviewing Apply Online – Submit your application online. Applications are reviewed on a rolling basis by our Talent Acquisition team. We read applications carefully, so thoughtful answers that explain your interests and motivations are useful. Technical Assessment – Selected candidates will complete a coding challenge focused on core programming and problem-solving skills . Interviews – Shortlisted candidates will take part in interviews, either on-site or via Microsoft Teams. We’ll explore your quantitative and technical thinking, how you approach unfamiliar problems and how you work with others. We also encourage candidates to take part in one of our Data Challenges . These are an opportunity to work on problems relevant to quantitative research and demonstrate your analytical and technical approach. Strong performance may lead to direct follow-up from our team: Challenge data (ens.fr) 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.

Location: London, Paris, New York 2027 – Internship or Graduate, FPGA Engineering Programmes offered: Final-year internship, penultimate-year internship, some permanent opportunities Location: London Programme duration: 3–6 months, or full-time graduate, starting in 2027 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, collaborative and demanding, with plenty of scope to ask questions, test ideas and take ownership. Strong performance during the internship may lead to consideration for a full-time graduate role. Your future role at QRT Throughout the recruitment process, we’ll consider your skills and interests alongside the problems our teams are working on, with the aim of finding the strongest fit. QRT’s FPGA team builds ultra-low-latency hardware for our trading systems. By implementing custom logic directly on FPGA devices, the team can process market data and execute orders with tight control over latency, throughput and system behaviour. The work sits at the boundary between hardware and software. We use SystemVerilog, C++ and Python to design, verify and integrate FPGA systems into our wider trading infrastructure. The problems are technically demanding: small design decisions can have measurable consequences, and performance needs to come with reliability. As an intern or graduate in the FPGA team, you will: Build production FPGA systems – Contribute to the design, development and optimisation of FPGA-based platforms used in live trading. Work across hardware and software – Use SystemVerilog, C++ and Python to build, test and refine high-performance, low-latency systems. Develop and verify new functionality – Implement FPGA features that improve how our systems process market data and execute orders, and build the tests needed to verify them. Integrate systems – Work with hardware and software engineers to connect FPGA components with QRT’s broader trading infrastructure. Analyse performance – Debug and profile designs, investigating latency, resource utilisation and other constraints to understand where improvements can be made. Work with modern FPGA technology – Gain hands-on experience with FPGA hardware, development tools and verification workflows used in low-latency trading. Explore new approaches – Contribute to research and development aimed at improving the performance and capabilities of our FPGA systems. Your present skillset Interest in technology: You enjoy understanding how systems work and have explored that interest through software or hardware projects, whether academic, personal or hobby-based. Formal Computer Science training is not essential. HDL experience: Experience or coursework using an HDL such as SystemVerilog, Verilog or VHDL. Programming: Experience with C++ and/or Python. Technical foundations: An understanding of digital logic design, computer architecture and high-speed interfaces. FPGA tools: Familiarity with FPGA development toolchains such as Xilinx Vivado or Intel Quartus is useful, but not essential. Problem solving: You can reason through technical problems methodically, troubleshoot designs and think about trade-offs between performance, resource utilisation and power efficiency. Mindset: Curious, proactive and comfortable asking questions. You look for opportunities to understand systems more deeply and improve how they perform. Approach: Self-motivated, thoughtful and comfortable taking ownership of a problem. Interviewing Application – Submit your application online. We review applications on a rolling basis, so applying early is recommended. Technical Assessment – Selected candidates will complete a technical interview with the relevant team . Interviews – Shortlisted candidates will take part in interviews, either on-site or via Microsoft Teams. We’ll explore your technical foundations, how you reason through engineering problems and how you work with others. 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.

Location: London, Paris 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. 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, open to penultimate students) 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. Depending on the team, relevant knowledge and experience may include: Programming or scripting in languages such as Python or Bash. Tools such as Git, SQL and GCC. Confidence working from the Linux command line, including familiarity with Linux/Unix system administration fundamentals. An understanding of storage concepts such as RAID, erasure coding, file systems and networking protocols. Knowledge of networking concepts including TCP/IP and Ethernet. Experience with monitoring and observability tools such as Grafana, Prometheus and PromQL. Hands-on experimentation with Linux, such as building Linux systems on laptops or Raspberry Pis or working with custom Android installations, particularly for on-premise Infrastructure roles. Mindset – Curious about how systems work and comfortable getting into the detail when something doesn’t behave as expected. You approach problems methodically, ask questions and look for practical ways to improve performance or reliability. Approach – Self-motivated, collaborative and comfortable taking ownership of a technical problem. Interviewing Application – Submit your application online. We review applications on a rolling basis, so applying early is recommended. Technical Assessment – Selected candidates will complete a coding challenge focused on core programming and problem-solving skills. Assessment Centre / Online Interviews – Shortlisted candidates will take part in interviews, either on-site at an assessment centre or via Microsoft Teams. We’ll explore your technical thinking, how you approach unfamiliar problems and how you work with others. 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.

Location: London, Paris, New York 2027 Internship – Security Engineer Programmes offered: Final-year internship, penultimate-year internship Location: London, Paris, New York Programme duration: 6-month internship or 12-month industrial placement, starting in 2027 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 working on production systems. The environment is technical and collaborative, with plenty of scope to ask questions, investigate unfamiliar problems and take ownership. Strong performance during the internship may lead to consideration for a full-time graduate role. Your future role at QRT Throughout the recruitment process, we’ll consider your skills and interests alongside the problems our teams are working on, with the aim of finding the strongest fit. As part of QRT’s Security team, you’ll help protect the systems, data and infrastructure behind our global research and trading activities. You’ll work closely with our Cloud, Infrastructure and Network Operations teams to design and implement security controls across a complex, high-performance technology environment. The team works across security engineering, detection and response, vulnerability management and security assurance. Rather than treating security as a separate layer, we work directly with engineering teams to understand how systems behave, identify weaknesses and build practical ways to prevent, detect and respond to threats. As an intern, you’ll contribute to real security problems and have opportunities to build tooling, investigate emerging attack techniques and improve how we automate security work at scale. Your current skillset Eligibility – Penultimate or final-year students pursuing a Bachelor’s, Master’s in a STEM discipline, such as Cyber Security, Informatics, Computing 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. Examples of relevant knowledge and experience include: An understanding of security principles and technologies such as firewalls, IDS/IPS, vulnerability scanning, password management, encryption and secure coding practices. Programming or scripting experience, particularly with Python or Bash. Confidence working from the Linux command line, including familiarity with Linux/Unix system administration fundamentals. An understanding of networking concepts, including TCP/IP and Ethernet. Experience with monitoring and observability tools such as Grafana, Prometheus and PromQL. Examples of the projects you may work on include: Triage agent development – Use MCP servers to build and improve a triage agent that supports cyber-security investigations. Detection engineering – Reproduce emerging attack techniques in segregated lab environments and test how effectively our detection systems identify them. Security assurance – Contribute to vulnerability research, security reviews and remediation testing, working with security and engineering teams to understand and address weaknesses. Security automation – Build tools and automation that make security assurance more scalable, consistent and effective. Mindset – Curious, proactive and comfortable asking questions. You’re willing to investigate unfamiliar systems, follow evidence and challenge assumptions when something doesn’t look right. Approach – Self-motivated, thoughtful and comfortable taking ownership of a problem. Interviewing Apply Online – Submit your application online. We review applications on a rolling basis, so applying early is recommended. Technical Assessment – Selected candidates will complete a technical interview with the relevant team . Assessment Centre / Online Interviews – Shortlisted candidates will take part in interviews, either on-site or via Microsoft Teams. We’ll explore your technical thinking, how you approach unfamiliar problems and how you work with others. 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.

Location: London, Paris, Wrocław, Zurich, Dubai, Aarhus, Amsterdam Programmes offered: Final-year internship, penultimate-year internship Location: London, Paris , Wrocław, Zurich, Dubai, Aarhus, Amsterdam Programme duration: 3–6 months or 12-month industrial placement , starting in 2027 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, collaborative and demanding, with plenty of scope to ask questions, test ideas and take ownership. Strong performance during the internship may lead to consideration for a full-time graduate role. Your future role at QRT As a Technology Intern, you’ll help build the systems, platforms and tools behind QRT’s research, trading and investment activities. You’ll work alongside experienced engineers, quantitative developers, researchers and traders, contributing to production technology and solving problems where performance, reliability and good engineering judgement matter. Depending on your interests and strengths, you may join one of two Technology disciplines. Software Engineer (London , Wrocław, Zurich ) Software Engineers build the technology that underpins QRT’s trading and investment activities. This includes the platforms and infrastructure that connect us to global markets, brokers and data providers, as well as the systems used for order generation, execution, analytics, risk management and P&L reporting. The engineering problems vary considerably in scale and shape. At one end, we build ultra-low-latency execution technology where small improvements can matter. At the other, we develop global, cross-asset platforms that need to process large volumes of data reliably and make complex information accessible to users across the firm. As an intern, you’ll work with experienced engineers, quantitative developers and researchers on a defined technical problem. You’ll be expected to understand the problem properly, make sensible engineering choices and build something useful. Examples of projects you may work on include: AI-Powered Static Analysis – Build a tool combining static analysis and large language models to identify double-deletion and memory-management issues in our public API. Exchange Simulator Advanced Order Support – Extend our Exchange Simulator to support market orders, time-in-force instructions and algorithmic orders, making strategy testing more representative of live trading. Risk Data Platform – Extend our risk data platform to provide the data required to support trading in a new trade type. Lightweight Trading UI – Create a lightweight trading interface with order entry, live market and position views, and clear visualisation of trading activity. Quantitative Developer (London, Paris, Wrocław, Dubai, Aarhus, Amsterdam) Quantitative Developers work at the intersection of research, trading and engineering. Sitting close to the trading desk, they work directly with researchers and traders to build the technology needed to explore ideas, analyse markets and run strategies in production. The role combines strong software engineering with an understanding of how technology can make quantitative research and trading more effective. That might mean building high-performance execution systems, improving research infrastructure, developing machine learning platforms or creating tools that make complex data easier to work with. You’ll work on live technical problems where performance, reliability and iteration speed all matter. It’s a collaborative role with direct exposure to quantitative research, financial markets and production trading systems. Examples of projects you may work on include: Real-Time Trading Systems – Build high-performance C++ systems for real-time trading, contributing to low-latency infrastructure and execution technology where every microsecond can matter. Quantitative Research Platforms – Help develop the platforms used for quantitative research across QRT, including machine learning systems and data pipelines that allow researchers to test and scale ideas efficiently. Research and Trading Tools – Design tools that simplify workflows, improve access to data and make complex information easier to understand through effective visualisation. You’ll work directly with traders, researchers and risk teams to understand their problems and build practical solutions. Your current skillset Eligibility: Penultimate or final-year students pursuing a Bachelor’s, Master’s in a STEM discipline, such as Computer Science, Physics, Mathematics or a related Engineering subject, on track for a 2:1 or above from a leading institution. Interest in technology: You enjoy solving technical problems and are curious about how systems work. You’re interested in building things, not just studying them. Software engineering experience: We value hands-on experience wherever you gained it — through personal projects, open-source contributions, hobbies, internships or academic work. Programming: Proficiency in C++, C# or Python. Tools: Familiarity with scripting languages such as Python or Bash, and tools and technologies including Git, SQL, GCC and Linux. Mindset: Curious, proactive and comfortable asking questions. You look for ways to make systems simpler, faster or more reliable and can turn those observations into practical improvements. Approach: Self-motivated, thoughtful and comfortable taking ownership of a problem. Interviewing Application – Submit your application online. We review applications on a rolling basis, so applying early is recommended. Technical Assessment – Selected candidates will complete a coding challenge focused on core programming and problem-solving skills. Assessment Centre / Online Interviews – Shortlisted candidates will take part in interviews, either on-site at an assessment centre or via Microsoft Teams. We’ll explore your technical thinking, how you approach unfamiliar problems and how you work with others. 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.

Location: Chicago 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. You will join the Core Trading Platform team, which is responsible for the design and operation of QRT’s global electronic trading infrastructure. This team builds and maintains the ultra-low latency systems that underpin real-time trading, managing performance-critical workflows across global markets. You will work closely with developers, traders, and operations to optimise system behaviour, reduce latency, and ensure platform reliability at scale. Your future role within QRT Design and implement low-latency trading systems on Linux, focused on throughput, reliability, and determinism Engineer scalable, high-performance distributed systems that support global real-time trading workflows Analyse system behaviour using low-level tools such as packet captures, core dumps, and runtime profilers Apply deep expertise in TCP, UDP, and multicast to understanding trade-offs in short-haul vs long-haul networks Continuously profile, benchmark, and optimise code to reduce latency and increase throughput Engage across the full software lifecycle: from architecture to debugging in live trading environments Your present skillset 2+ years of professional C++/C development experience on Linux, including modern C++ and multithreading Strong expertise in TCP, UDP, multicast, and performance trade-offs in low-latency networks Experience building and operating high-throughput distributed systems in production Familiarity with scalable I/O models (e.g., epoll, io_uring), lock-free structures, and concurrent programming Deep attention to detail with a rigorous approach to performance troubleshooting and optimisation Proficiency in system-level tools (e.g., gdb, perf, tcpdump, valgrind, wireshark) Comfortable working autonomously and taking ownership from problem to solution Scripting experience (e.g., Python, Bash) and exposure to CI/CD or observability tooling is a plus Prior exposure to electronic trading or exchange-facing systems is advantageous Base salary range for this position is $150,000 to $220,000 per year. QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

Location: London 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. You will join QRT as the Identity and Access Management Lead, owning the firm’s global identity and access security capability. This is a hands-on leadership role in which you will set the strategy, lead programmes, and remain close to the technology to ensure solutions are secure, automated, and practical for QRT’s engineering environment. Your Future Role within QRT Lead QRT’s IAM and IGA strategy, architecture, roadmap, and delivery. Develop identity lifecycle management, application onboarding, entitlement governance, and access certification. Redesign Active Directory groups, legacy permissions, and access models, establishing clear ownership of applications, roles, entitlements, and access decisions. Develop pragmatic role- and attribute-based access models and improve the automation and accuracy of joiner, mover, and leaver processes. Own the global PAM programme, including the continued development and adoption of PrivX. Redesign privileged access to production, infrastructure, cloud, and trading-critical environments. Reduce standing privileges through controlled, time-bound, and auditable access, with effective controls for administrative accounts, emergency access, and privilege escalation. Own the enterprise secrets-management programme and HashiCorp Vault platform. Define how credentials, certificates, API keys, and other secrets are created, stored, rotated, and revoked. Reduce embedded, shared, and long-lived credentials, while establishing governance for service accounts, workloads, applications, and AI-agent identities. Lead authentication and authorisation programmes across the workforce, infrastructure, cloud, and internally developed applications. Develop strategies and reusable patterns for SSO, MFA, passwordless authentication, phishing-resistant credentials, applications, APIs, platforms, and production systems. Lead and develop the IAM team, manage specialist partners and vendors, and work closely with Security, Infrastructure, Cloud, Engineering, application owners, and business teams. Maintain a clear roadmap, define meaningful measures, communicate progress and risks, and support security incidents, audits, and regulatory reviews involving identity or access. Your Present Skillset Strong experience leading IAM, IGA, PAM, or identity-security engineering in a complex technology environment. Deep knowledge of identity governance, privileged access, secrets management, authentication, and authorisation. Practical experience with SailPoint, Active Directory, Entra ID, Okta, PAM technologies, and HashiCorp Vault. Experience redesigning production access and implementing least-privilege and time-bound access models. Strong understanding of human, service, workload, and machine identities. Experience delivering SSO, MFA, passwordless authentication, and modern application-authorisation models. Strong technical capability across APIs, automation, scripting, and system integration. A good understanding of Windows, Linux, cloud, and modern software-delivery environments. Experience leading technical teams and turning complex security risks into practical engineering priorities. 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 offer initiatives and programmes to enable employees to achieve a healthy work-life balance.

Location: Hong Kong & Sydney Location: Hong Kong and Sydney Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager operating across all liquid asset classes worldwide. We are a technology- and data-driven organisation applying a scientific approach to investing. By combining data, research, technology and trading expertise, we foster a collaborative environment that enables us to solve complex challenges. Our culture of innovation drives our ambition to deliver high-quality returns for our investors. Your future role at QRT We are looking for an experienced Trading Systems Software Engineer to help build the applications, platforms and engineering capabilities that support QRT’s global trading environment. This is a broad software engineering role spanning application development, distributed systems, cloud technology, deployment automation and production engineering. You will design and build software used by traders, quantitative researchers, operations teams and other engineers across the firm. The focus extends beyond delivering individual features. You will identify opportunities to create scalable, reusable capabilities that improve how trading systems are developed, deployed, monitored and operated across multiple teams and trading desks. Working closely with both technical and business stakeholders, you will gain a detailed understanding of trading workflows and translate complex requirements into reliable, maintainable and well-designed software. What you’ll do Design, develop and maintain production-grade applications, services and APIs supporting QRT’s trading platform. Build shared platforms and reusable capabilities that can be adopted across multiple trading desks and engineering teams. Develop modern web applications and operational tools that improve visibility, control and efficiency across trading workflows. Design scalable distributed and event-driven systems that integrate with trading platforms, market data services and internal infrastructure. Build deployment tooling, release automation and self-service capabilities that make software easier and safer to deploy and operate. Develop automated workflows for data processing, operational tasks and engineering processes using technologies such as Apache Airflow. Partner with traders, quantitative researchers and operations teams to understand their needs and solve practical business problems. Design software for latency-sensitive environments, balancing performance with reliability, scalability and operational simplicity. Build observable and resilient systems with appropriate monitoring, alerting, recovery and failure-handling capabilities. Work alongside infrastructure, cloud and DevOps engineers to deploy and support software across global production environments. Contribute to technical design and architectural decisions, evaluating new technologies where they can deliver meaningful value. Take ownership of software throughout its lifecycle, from initial design and implementation through to production support and continuous improvement. Your present skillset You will likely have: At least five years of experience developing and supporting production-grade software. Strong programming and software engineering skills in one or more languages such as Python, Java, Go, Node.js or C++. Experience designing maintainable, testable and scalable applications and services. A strong understanding of software design principles, data structures, algorithms and engineering fundamentals. Experience building RESTful APIs, distributed systems or event-driven architectures. A good working knowledge of Linux environments. Experience working with relational databases such as PostgreSQL or MySQL. Exposure to containerisation, orchestration and delivery technologies such as Docker, Kubernetes and CI/CD pipelines. Experience with public cloud technologies, preferably AWS. An understanding of messaging technologies such as Kafka or RabbitMQ. Experience considering reliability, observability, performance and failure recovery when designing production systems. Strong analytical and problem-solving skills, with the ability to make sound engineering decisions and explain the associated trade-offs. The ability to work effectively with both technical and non-technical stakeholders. Experience in one or more of the following areas would be advantageous: Apache Airflow or a comparable workflow-orchestration platform. React, Vue, Angular or another modern front-end framework. Deployment automation, developer platforms or operational tooling. Market data, order management systems, execution management systems or electronic trading platforms. Financial markets or another complex, time-sensitive production environment. You do not need to have worked in financial services. We are interested in engineers who are curious, technically strong and motivated to understand how technology supports a global trading business. Your way of working You will thrive in this role if you: Enjoy designing systems as well as implementing them. Think about scalability, reliability and maintainability from the outset. Look for opportunities to automate repetitive work and improve engineering processes. Take ownership and remain accountable for the quality of your software in production. Work collaboratively and seek to understand the needs of the people using the systems you build. Approach technical decisions pragmatically and can balance competing business and engineering priorities. Are intellectually curious and enjoy learning about unfamiliar technologies and business domains. Maintain high standards while remaining open to feedback and different perspectives. Why join QRT? Technology sits at the heart of QRT. You will work alongside talented traders, quantitative researchers and engineers, building software that directly supports our global trading activities. The role offers exposure to a broad range of engineering challenges, from cloud-native services and distributed systems to trading applications, deployment platforms and operational tooling. You will have the autonomy to shape solutions, contribute to architectural direction and see your work used every day by teams across the firm. If you enjoy building scalable systems and creating software that makes engineers, traders and operational teams more effective, you will have the opportunity to make a meaningful impact at QRT.

Location: London 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 QRT’s 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. We are looking for a developer with 3+ years of experience in a quant trading environment to work directly with traders and quant researchers. Your future role within QRT Key member to the success of high-frequency and low latency crypto trading Enrich and implement alpha and trading algorithms Implement specific market rules for the main crypto markets Collaborate with the traders and quant researchers on providing efficient research platform and tools Your present skillset Computer Science degree or equivalent Strong C++ 20/23 development experience on a Linux environment Interest in solving technical problems, along with ability to implement robust resilient and flexible solutions Familiar with HPC in Cloud environment, good level of Python Good communication skills in a dynamic and international environment 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.

Location: London 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 QRT’s 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. You will work within a data function responsible for making complex financial datasets accessible and reliable for research and trading. You will collaborate directly with Quantitative Researchers and Traders to understand data requirements, onboard new sources and build datasets that support systematic strategies and discretionary trading decisions. Your future role within QRT Collaborate with Quantitative Researchers and Traders to design datasets that support systematic strategies and discretionary trading decisions Extract, clean and aggregate data from a wide range of raw sources and formats using QRT’s data framework Manage the full process of onboarding new datasets, from initial assessment through to production Investigate and resolve data issues to reduce the time required to make new datasets available to users Develop robust data extraction processes with a strong focus on correctness and data quality Explore and implement new approaches to data extraction that improve the tools available for onboarding complex datasets Your present skillset 3+ years of experience in Data Engineering or a similar role working with financial data Advanced Python development skills, including experience with libraries such as Pandas, Polars and NumPy Strong focus on correctness, with the ability to critically assess code and data quality regardless of source Experience working with SQL and relational databases Experience working with both traditional and alternative financial datasets Demonstrated interest in financial markets and the application of data to investment research and trading Experience within quantitative finance is beneficial Excellent communication skills with the ability to collaborate with Quantitative Researchers, Traders, Engineers, management and external data providers Ability to operate effectively in a high performance environment with rapid delivery cycles 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.

Location: London 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. The Network team is responsible for the architecture, engineering and operation of QRT’s global trading and enterprise networks. The Principal Network Engineer is a senior individual contributor responsible for deep technical leadership, complex problem-solving and continuous engineering improvement. Working closely with network leadership and engineering teams, you will ensure complex technical problems are resolved effectively, architectural standards are translated into usable engineering practices, and the network becomes increasingly scalable, supportable and resilient without creating individual points of dependency. Your future role within QRT: Lead investigations into complex performance, latency, resilience and operational issues. Act as a senior technical escalation point for network teams. Turn architecture standards into implementation patterns, automation, validation, documentation and runbooks. Lead or support complex changes, migrations and technical improvement work. Evaluate new technologies and improve existing designs and operating practices. Implement effective instrumentation and use operational data to identify problems and improvements. Mentor engineers and spread knowledge across the function. Your Present Skillset: Deep hands-on experience designing, operating and troubleshooting complex networks. Strong knowledge of WAN, data-centre networking, BGP, multicast, and ultra low-latency environments. Strong packet-analysis, telemetry and structured troubleshooting skills. Strong knowledge of financial market architectures Experience with automation, source-controlled configuration, validation and monitoring. Knowledge of FPGA-connected network paths. Experience mentoring engineers and influencing technical decisions. 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.