Overview
As Senior Lead ML Engineer, you will architect and deliver production-scale ML platforms that power a large-scale matching system. You will lead ML lifecycle governance, tooling, and operational excellence, working across data pipelines, model training, and deployment. You’ll build reliable, low-latency inference services and drive continuous improvement in ML workloads. This is a hands-on leadership role shaping how ML enables our financial market solutions at scale. You’ll collaborate with cross-functional teams to turn data into trusted, impactful models.
Pay / Benefits
- healthcare
- retirement planning
- paid volunteering days
- wellbeing initiatives
Responsibilities
- Define end-to-end ML architectures covering data pipelines, feature engineering, model training, deployment, inference, monitoring, and telemetry
- Set engineering standards and promote operational excellence across ML platforms
- Implement feature stores, lakehouse architectures, and data-quality frameworks
- Coach engineers, review designs, and steer technical direction
- Lead SageMaker-based workflows (pipelines, training, processing, model registry, endpoints) and related deployment practices
- Drive CI/CD, infrastructure as code, and automated model retraining
- Establish observability, drift detection, experimentation, and performance engineering for ML systems
- Manage multi-account AWS deployments and cross-account ML platform orchestration
Key requirements
- Enterprise-scale ML platform design and delivery, preferably with AWS SageMaker
- End-to-end ML solution delivery from data ingestion to production deployment and monitoring
- Experience building low-latency inference services and operating ML workloads at scale
- Proven ability to address scaling, reliability, and operational challenges in enterprise ML
- Deep hands-on expertise with SageMaker Pipelines, training, processing, model registry, endpoints, and monitoring
- Experience with CI/CD, IaC, model lifecycle management, and automated retraining
- Strong knowledge of model governance, explainability, traceability, auditability (SHAP, Model Cards) and documentation
- Coaching and mentoring of engineers
- Technical leadership and collaboration across teams
- Strong communication and design_review capabilities
- AWS SageMaker (Pipelines, Training, Processing, Registry, Endpoints, Monitoring)
- Feature stores and lakehouse architectures
- MLOps and deployment automation
Senior Lead Machine Learning Engineer in London employer: London Stock Exchange Group
At London Stock Exchange Group, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Lead Java Engineer in our Risk Platform team, you will have access to unparalleled growth opportunities, working alongside industry experts in a vibrant London setting that champions diversity and professional development. Join us to make a meaningful impact while enjoying competitive benefits and a supportive environment that values your contributions.
Contact Details:
London Stock Exchange Group Recruitment Team
