Lead Machine Learning Engineer
LSEG (London Stock Exchange Group)
full-time
Posted on:
Location Type: Office
Location: London • United Kingdom
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Job Level
Tech Stack
About the role
- Design, build, and productionise machine learning models that power the matching platform.
- Work across the full ML lifecycle—feature engineering, model development, training pipelines, deployment automation, inference optimisation, monitoring, and explainability.
- Make strong hands-on technical contributions, take ownership of key components of the ML platform.
- Collaborate closely with data scientists, platform engineering, and product teams.
- Help improve MLOps practices, enhance observability, and ensure ML systems meet security, performance, and compliance standards.
Requirements
- Strong experience delivering production ML systems end-to-end.
- Proficiency with AWS SageMaker (training jobs, processing, endpoints, Model Registry).
- Excellent Python skills and experience with ML Models such as PyTorch, TensorFlow, or XGBoost.
- Hands-on experience with model explainability tools such as SHAP.
- Understanding of low-latency, real-time inference patterns and optimisation techniques.
- Experience implementing drift detection, monitoring, and telemetry.
- Working knowledge of ML governance, data privacy, and secure ML practices.
- Strong understanding of MLOps, CI/CD, and automation for ML workflows.
Benefits
- Healthcare
- Retirement planning
- Paid volunteering days
- Wellbeing initiatives
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningfeature engineeringmodel developmenttraining pipelinesdeployment automationinference optimisationmodel explainabilityPythonAWS SageMakerMLOps
Soft Skills
collaborationownershiptechnical contributions