Senior Lead Machine Learning Engineer
AI in this role
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
The Role:
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).
You will provide technical leadership across ML lifecycle, including defining architecture, engineering standards, MLOps practices, and governance frameworks for a large-scale matching platform. This is a hands-on lead role requiring recent expertise in building, deploying, monitoring, and operating ML systems in production.
Essential Experience
- Demonstrable success designing and delivering enterprise-scale ML platforms and products (ideally using AWS SageMaker).
- Proven experience delivering ML solutions from data ingestion and feature engineering through to production deployment, monitoring, and continuous improvement.
- 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.
Technical Leadership & Architecture
- Defining end-to-end ML architectures spanning data pipelines, feature engineering, model training, deployment, inference, monitoring, and telemetry.
- Establishing engineering standards and operational excellence.
- Implementing feature stores, Lakehouse architectures, and enterprise data quality frameworks.
- Coaching engineers, reviewing designs, and driving technical direction.
MLOps, Deployment & Operations
- Deep hands-on experience with SageMaker Pipelines, Training, Processing, Model Registry, Endpoints, Monitoring, and deployment workflows.
- CI/CD, infrastructure as code, model lifecycle management, and automated retraining.
- Observability, drift detection, experimentation, and performance engineering.
- Multi-account AWS deployments and cross-account ML platforms.
Model Development, Governance & Explainability
- Deep experience applying a wide range of machine learning techniques to real-world business problems, including using models such as XGBoost and deep learning approaches using frameworks such as PyTorch or TensorFlow, taking solutions from experimentation through to production deployment and operation.
- Strong knowledge of model governance, explainability, traceability, auditability, SHAP, Model Cards, and model documentation practices.
- Experience establishing governance frameworks that ensure models are explainable, reproducible, and compliant with enterprise standards.
Testing, Validation & Performance Engineering
- Lead validation strategies using golden datasets, behavioural tests, and benchmark suites.
- Architect performance testing for latency‑sensitive inference paths and model hot paths.
- Establish standards for A/B testing, shadow deployments, canary rollouts, and controlled experiments.
Nice to Have
- 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.
Career Stage:
ManagerLondon 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.
Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject.
If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.
How we rate this
Senior Lead Machine Learning Engineer at LSEG rates 92 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through how you've used PyTorch in your day-to-day work.
- What are the limits of TensorFlow that you've run into, and how did you work around them?
- What's a project where you used XGBoost hands-on?
- Walk me through how you've used Sagemaker in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: ML Ops, PyTorch, TensorFlow, XGBoost, and Sagemaker. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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