Overview
In this role you will help lead the development and global rollout of a research framework for training models used in production trading. You will partner with Quantitative Researchers to test hypotheses and build data-driven trading strategies, while expanding the framework to integrate with production systems. This is a chance to shape a scalable, data-driven research platform at Flow Traders in London, combining research with production deployment to drive alpha signals.
Responsibilities
- Lead development and rollout of the research framework for training models and integrating it with the production platform
- Collaborate with Quantitative Researchers to test hypotheses and refine data-driven trading strategies and alpha signals
- Design and implement end-to-end ML pipelines, including data preprocessing, model training, deployment, and monitoring
- Support modernization of software development practices and tools (Agile, version control, CI/CD, observability)
- Contribute to the global deployment and reliability of the research framework across data sources and platforms
Key requirements
- Advanced degree (Master’s or PhD) in Machine Learning, Statistics, Physics, Computer Science or similar
- 8+ years of hands-on experience in MLOps, Research Engineering, or ML Research
- Strong background in mathematics and statistics
- Proficiency in Python and libraries such as numpy, pytorch, polars, pandas, and ray
- Experience in end-to-end ML pipelines (data preprocessing, training, deployment, monitoring)
- Understanding of modern software development practices and tools (Agile, version control, automated testing, CI/CD, observability)
- Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)
- Collaborative mindset and ability to work with cross-functional teams
- Strong analytical and problem-solving abilities
- Proactive communication and clear technical storytelling
- Python programming
- numpy
- pytorch
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