Lead Machine Learning Engineer

About Us:

LSEG (London Stock Exchange Group) is more than a diversified global financial markets infrastructure and data business. We are dedicated, open-access partners with a dedication to excellence in delivering the services our customers expect from us. With extensive experience, deep knowledge and worldwide presence across financial markets, we enable businesses and economies around the world to fund innovation, manage risk and create jobs. It’s how we’ve contributed to supporting the financial stability and growth of communities and economies globally for more than 300 years. Through a comprehensive suite of trusted financial market infrastructure services – and our open-access model – we provide the flexibility, stability and trust that enable our customers to pursue their ambitions with confidence and clarity.

LSEG is headquartered in the United Kingdom, with significant operations in 70 countries across EMEA, North America, Latin America and Asia Pacific. We employ 25,000 people globally, more than half located in Asia Pacific. LSEG’s ticker symbol is LSEG.

Our People:

People are at the heart of what we do and drive the success of our business. Our culture of connecting, creating opportunity and delivering excellence shape how we think, how we do things and how we help our people fulfil their potential. We embrace diversity and actively seek to attract individuals with unique backgrounds and perspectives. We break down barriers and encourage teamwork, enabling innovation and rapid development of solutions that make a difference. Our workplace generates an enriching and rewarding experience for our people and customers alike. Our vision is to build an inclusive culture in which everyone feels encouraged to fulfil their potential.

We know that real personal growth cannot be achieved by simply climbing a career ladder – which is why we encourage and enable a wealth of avenues and interesting opportunities for everyone to broaden and deepen their skills and expertise. As a global organisation spanning 70 countries and one rooted in a culture of growth, opportunity, diversity and innovation, LSEG is a place where everyone can grow, develop and fulfil your potential with meaningful careers.

Role Summary

We are looking for a Lead Machine Learning Engineer (SageMaker, MLOps, Explainability) to design, build, and productionise machine learning models that power our new matching platform. You will work across the full ML lifecycle—feature engineering, model development, training pipelines, deployment automation, inference optimisation, monitoring, and explainability.

In this role, you will make strong hands‑on technical contributions, take ownership of key components of the ML platform, and collaborate closely with data scientists, platform engineering, and product teams. You will help improve our MLOps practices, enhance observability, and ensure that our ML systems meet standards for security, performance, and compliance.

This role is suited to an experienced engineer who can deliver production‑grade ML systems, influence design decisions, and maintain high technical standards, while still working primarily as an individual contributor.

Key Responsibilities

Feature Engineering

• Build and maintain scalable feature pipelines within data lakehouse architectures.
• Develop fallback feature flows (e.g., export paths).
• Implement robust data quality checks and contribute to the adoption of feature store patterns.

Model Development & Scoring

• Develop ranking, scoring, and entity‑similarity models fit for the matching platform.
• Implement calibrated confidence scores, thresholds, and model scoring logic.
• Use modern ML Model frameworks such as PyTorch, TensorFlow, or XGBoost.
• Collaborate with data scientists on model design and performance improvements.

Explainability & Reason Codes

• Apply SHAP or similar techniques to generate interpretable model explanations.
• Produce reason codes suitable for business, operational, or regulatory consumption.
• Ensure explainability outputs are versioned, tested, and integrated into inference workflows.

ML Deployment & MLOps

• Build and maintain training, processing, and inference pipelines using AWS SageMaker.
• Integrate models with model registries and implement automated deployment patterns.
• Support rollback and redeploy mechanisms for weight updates or model iterations.
• Contribute to CI/CD improvements for ML-specific workflows.

Inference Runtime & Cross‑Account Serving

• Deploy and optimise low‑latency, real‑time inference endpoints.
• Implement secure AWS IAM patterns supporting cross‑account inference access.
• Build telemetry for request logging, performance tracking, and latency monitoring.
• Solve runtime issues and optimise throughput and cost.

Monitoring, Drift Detection & Telemetry

• Implement feature drift and concept drift monitoring.
• Build dashboards, alerts, and critical performance metrics to detect model degradation.
• Develop telemetry and logging frameworks that respect data minimisation principles.

Security, Compliance & ML Governance

• Apply procedures for data handling, encryption, PII minimisation, and auditability.
• Produce Model Cards, documentation, and lineage artefacts needed for governance.
• Ensure that ML pipelines meet internal standards for reproducibility and traceability.

Testing, Validation & Performance

• Conduct validation of models using golden datasets, baseline tests, and regression testing.
• Optimise models for latency‑sensitive inference paths.
• Support A/B tests, shadow deployments, and progressive rollout strategies.

Core Skills & Experience

Essential

• 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.

Nice to Have

• Experience working with feature stores or Lakehouse data architectures.
• Previous experience with ranking, matching, or similarity models.
• Familiarity with cross‑account AWS IAM patterns and multi-account design.
• Bachelors in a STEM subject, e.g. mathematics, physics, engineering, computer science, or adjacent degrees.

Career Stage:

Senior Associate

London Stock Exchange Group (LSEG) Information:

Join us and be part of a team that values innovation, quality, and continuous improvement. If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.

LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.

Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.

Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.

We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.

You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives. Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering.

LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.

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