Job Description

Programme duration: 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 Machine Learning Engineer at QRT, you will contribute to building the systems used to evaluate and compare LLMs across a range of tasks and datasets. Design evaluation pipelines, define scoring methodologies, and develop the services that run, track, and reproduce experiments at scale. Integrate new models into a unified framework and optimize evaluation workflows for performance and reliability.

Your present skillset 

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  Strong Python skills, with experience building reliable and maintainable systems.

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  Solid software engineering fundamentals, including APIs, testing, and modular design.

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  Experience working with data pipelines and experimentation workflows.

• Excellent communication skills - you will interact directly with Traders and Researchers. 

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  Strong analytical and problem-solving skills, with a structured approach to ambiguous problems.

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  Interest in large language models (LLMs), machine learning systems, and evaluation methodologies.

Preferred qualifications (a plus):

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  Experience with LLM tooling or frameworks (e.g. Hugging Face, OpenAI APIs, vLLM, or similar).

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  Familiarity with evaluation or benchmarking frameworks (e.g. lm-eval, HELM, or custom evaluation pipelines).

• Experience building backend services (FastAPI, Flask, or similar) and job orchestration systems.

• Exposure to distributed systems, parallel computing, or GPU-based workloads.
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  Experience with experiment tracking tools (e.g. MLflow, Weights & Biases) or similar systems.
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  Interest in model evaluation, robustness, and real-world performance of machine learning systems.

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.