Quantitative Developer – Machine Learning Platform Engineer

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 a Machine Learning Platform Engineer, where you will support platform tooling, infrastructure scalability, and best practices for model deployment across research and trading teams with emphasis on Machine Learning, Artificial Intelligence and Large Language Model.

This role combines solution architecture, software development and infrastructure engineering on the context of Machine Learning and AI workflows. The scope includes automation engineering using AI agents, as well as training support for internal users. You’ll work closely with a variety of teams to increase adoption of robust and scalable ML workflows, educate interns and develop training opportunities.

Your future role within QRT

• Deploy and educate on automation & CI/CD workflows for Machine Learning.
• Train Researchers and Developers on clean code design and software architecture.
• Support campus events, hackathons and coding challenges.
• Maintain and contribute to internal training codebases and documentation
• Deploy and educate on tools for consistent development environments, as well as AI agent assisted software development.
• Collaborate with internal teams to scale platform capabilities and increase reliability

Your present skillset

• Experience with object-oriented programming in Python and/or C++, applying SOLID principles
• Knowledge of CI/CD systems, Git workflows, and infrastructure-as-code tooling
• Familiarity with cloud infrastructure technologies (e.g. Docker, Terraform, Kubernetes) and cloud services.
• Understanding of MLOps practices and tools (e.g. MLflow, Airflow); knowledge of LLMops is a plus
• Experience with AI agents such as Cursor, Claude Code, Codex etc.
• Strong communication skills and a collaborative mindset focused on enablement
• Interest in teaching and improving engineering standards across teams

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.