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 that 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. This highly hands-on, principal-level role combines architectural vision with deep practical expertise in ML engineering and AWS-native MLOps. You will mentor engineers, influence product and architectural decisions, and ensure ML systems operate reliably at scale, underpinned by a robust governance and compliance framework.

LSEG is a diversified global financial markets infrastructure and data business with over 300 years of history. We enable businesses and economies worldwide to fund innovation, manage risk, and create jobs. Our culture embraces diversity, innovation, and continuous growth, providing meaningful career opportunities in a collaborative 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 and motivated ML engineer with a passion for building scalable, secure, and compliant ML systems. You thrive in a collaborative environment, enjoy mentoring others, and have a strong commitment to engineering excellence and innovation. You embrace diversity and are eager to contribute to a culture of growth and inclusion.

Qualifications
Bachelor's degree in a STEM subject such as mathematics, physics, engineering, computer science, or related fields is required. A Master's or PhD or equivalent experience in STEM is desirable but not essential. Experience with feature store adoption, ranking/search relevance, entity matching, or similarity modelling is a plus. Knowledge of distributed training, GPU/accelerator optimisation, and scaling strategies is advantageous.