Location
5 Canada Square, London

Hours
Full Time

Salary
Negotiable

About the Role
London Stock Exchange Group (LSEG) is seeking a Principal Machine Learning Engineer to provide technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring models are scalable, secure, explainable, and governed to enterprise-grade standards. You will contribute to the strategic direction of the ML platform—spanning data pipelines, model development, deployment automation, inference runtime design, telemetry, drift detection, and cross-account productionisation. You will mentor engineers, influence product and architectural decisions, and ensure ML systems operate reliably at scale with robust governance and compliance frameworks. This is a highly hands-on, technical, principal-level role combining architectural vision with deep practical expertise in ML engineering and AWS-native MLOps.

Company Overview
LSEG is a diversified global financial markets infrastructure and data business dedicated to excellence and open-access partnership. With over 300 years of history, LSEG supports financial stability and growth worldwide through trusted infrastructure services. Headquartered in the UK with operations in 70 countries, LSEG employs 25,000 people globally. Our culture embraces diversity, innovation, and personal growth, enabling employees to fulfil their potential in a collaborative and inclusive environment.

Experience
- Proven track record architecting and delivering production ML systems at scale in enterprise environments
- Deep expertise with AWS SageMaker (training, processing, pipelines, endpoints, registry) and complementary AWS services
- Expert-level Python and ML model frameworks such as PyTorch, TensorFlow, and XGBoost
- Strong thought leadership in MLOps automation, CI/CD for ML, and model lifecycle management
- Advanced experience designing explainability systems, reason codes, and governance artefacts
- Expertise in low-latency inference architectures and real-time model serving
- Strong grounding in drift detection, telemetry pipelines, observability patterns, and model QA
- Experience shaping ML security practices including cross-account IAM, data minimisation, and PII-safe design
- Ability to influence architecture, mentor senior engineers, and set long-term technical direction

About You
You are a highly skilled ML engineer with a passion for technical leadership and innovation. You thrive in complex environments and enjoy mentoring teams and influencing architectural decisions. You embrace best practices in security, governance, and compliance and are motivated by delivering scalable, reliable, and explainable ML systems. You value collaboration and continuous improvement within a diverse and inclusive culture.

Qualifications
- Bachelor’s degree in a STEM subject such as mathematics, physics, engineering, computer science, or related field
- Masters, PhD, or equivalent experience in STEM desirable but not essential
- Nice to have: experience building or leading feature store adoption, background in ranking, search relevance, entity matching or similarity modelling, experience designing or governing multi-account AWS ML platforms, knowledge of distributed training, GPU/accelerator optimisation, and scaling strategies