Machine Learning Engineer - Quantitative Trading Firm - London
Machine Learning Engineer - Quantitative Trading Firm - London
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
This is a remote position.
We re seeking a highly skilled Machine Learning Engineer to join a dynamic team at a leading quantitative trading firm known for leveraging technology to drive global trading strategies. This role offers a unique opportunity to work at the intersection of cutting-edge machine learning research and high-performance trading systems.
As part of the ML team you ll be responsible for developing deploying and optimizing machine learning models that enhance decision-making across multiple asset classes. You will collaborate closely with researchers data scientists and software engineers to build robust scalable ML infrastructure that supports rapid experimentation and production-level performance.
The ideal candidate combines a strong theoretical understanding of machine learning with hands-on experience in building end-to-end systems. You ll apply your expertise in various ML techniques ranging from deep learning and gradient-boosted trees to ensemble methods to solve complex problems in a fast-paced data-rich environment.
You will also focus on refining research workflows improving model reproducibility and ensuring that models integrate smoothly with trading infrastructure.
Design build and maintain scalable training and inference pipelines for ML models used in trading decisions
Collaborate across teams to translate research innovations into production-ready systems
Optimize algorithms and model architectures to maximize predictive accuracy and latency requirements
Contribute to the continuous improvement of tools and processes that accelerate ML research cycles
Analyze large complex datasets to extract insights and support data-driven decision-making
Requirements
- A strong background in machine learning statistics or a related quantitative field is essential.
- Experience with ML frameworks such a PyTorch or Tensorflow
- Proficiency in Python and/or C for high-performance computing is required.
- Candidates should have a solid foundation in mathematics including linear algebra optimization and probability theory.
- Familiarity with building reproducible research pipelines and managing codebases collaboratively is important.
- Comfort working in Linux environments and cloud or distributed computing platforms is expected.
A strong background in machine learning, statistics, or a related quantitative field is essential. Experience with ML frameworks. Proficiency in Python and/or C++ for high-performance computing is required. Candidates should have a solid foundation in mathematics, including linear algebra, optimization, and probability theory. Familiarity with building reproducible research pipelines and managing codebases collaboratively is important. Comfort working in Linux environments and cloud or distributed computing platforms is expected.
Employment Type
Full Time
Company Industry
Financial Services / Insurance Agencies and Brokerages / Investment Banking
