Senior Lead Machine Learning Engineer
Confirmed on the employer's own hiring board on Oct 26, 2026. First seen by Alion on Oct 10, 2026. London Stock Exchange scores A on the Alion truth index.
Join our team as a Senior Lead Machine Learning Engineer, where you will provide technical leadership across the entire ML lifecycle. You will define architecture, engineering standards, MLOps practices, and governance frameworks for a large-scale matching platform. Your responsibilities will include establishing engineering standards, implementing feature stores and Lakehouse architectures, coaching engineers, and driving technical direction. You should have deep hands-on experience with SageMaker and a strong knowledge of model governance and explainability. This is a hands-on lead role requiring recent expertise in building, deploying, monitoring, and operating ML systems in production.
Missions
- Provide technical leadership across the machine learning lifecycle, including defining architecture, engineering standards, MLOps practices, and governance frameworks for a large-scale matching platform.
- Define end-to-end machine learning architectures spanning data pipelines, feature engineering, model training, deployment, inference, monitoring, and telemetry.
- Establish engineering standards and operational excellence, implement feature stores, Lakehouse architectures, and enterprise data quality frameworks.
Profil recherché
- We're looking for a Senior Lead ML Engineer with a proven track record of delivering successful, production-scale machine learning solutions (ideally on AWS SageMaker)- This is a hands-on lead role requiring recent expertise in building, deploying, monitoring, and operating ML systems in production
- Demonstrable success designing and delivering enterprise-scale ML platforms and products (ideally using AWS SageMaker)
- Experience building reliable, low-latency inference services and operating ML workloads at scale
- Proven experience solving scaling, reliability, and operational challenges for enterprise ML systems
- Proven experience delivering ML solutions from data ingestion and feature engineering through to production deployment, monitoring, and continuous improvement
- Background in ranking, search relevance, entity matching, or similarity modelling
- Experience in KYC, Sanctions Screening or Compliance domains
- Knowledge of distributed training, GPU/accelerator optimisation, and scaling strategies
- Bachelors in a STEM subject, e.g. mathematics, physics, engineering, computer science, or adjacent degrees
- Masters or PhD or equivalent experience in STEM