LBG

Machine Learning Engineer

London Full time

End Date

Tuesday 02 December 2025

Salary Range

£87,552 - £97,280

We support flexible working – click here for more information on flexible working options

Flexible Working Options

Job Share

Job Description Summary

.

Job Description

JOB TITLE: Machine Learning Engineer.

SALARY: £70,900pa to £107,000pa (dependent on location and experience) plus an extensive benefits package.

LOCATION:  London, Bristol, Manchester, Chester.

HOURS: 35 hours, full time.

WORKING PATTERN: Our work style is hybrid, which involves spending at least two days per week, or 40% of your time, at one of the above listed hubs.

Why Lloyds Banking Group?

Like the modern Britain we serve, we're evolving. Investing billions in our people, data and tech to transform the way we meet the everchanging needs of our 26 million customers. We're embracing collaborative, agile ways of working, to help us deliver the best outcomes for our colleagues, customers and businesses. We're growing with purpose. Join us on our journey and you will too!

Want to hear more?

As a Machine Learning (ML) Engineer, you’ll play a meaningful role in developing, operating and maintaining ML solutions across Consumer Lending. You’ll work on different projects with a wide variety of colleagues to understand how we can apply the latest ML thinking to deliver value.

Working in our growing team enables you to get close to and understand how the business operates, how we serve our customers and the role that Data Science and ML can play in making things better for LBG and its customers – and it’s this proximity to the business that sets us apart.

Your role will evolve as the team matures, so we’d love to hear from applicants who are highly motivated, curious, keen to learn and open to trying new ways of working. We’re also looking for applicants with a proven background in working with large-scale applications and data platforms.

Key activities in the role:

  • Develop and maintain end-to-end ML systems in Python alongside our data scientists, including engineering new features, specifically providing expert ML input.

  • Maintain and refine high quality, reusable data and ML pipelines at scale.

  • Play a leading role in incident management and resolution, working closely with the strategic platform team and business partners.

  • Work collaboratively with others to identify, develop and implement new solutions that deliver customer and business value.

  • Promote high quality ML practices alongside maintaining an effective control environment, sharing knowledge with others and offering technical leadership or support as needed.

  • Proactively seek opportunities to improve solutions and present concrete plans to deliver these.

  • Deliver in line with LBG data science, model governance and risk management policies and procedures, maintaining constructive relationships with specialist colleagues in these areas.

  • Grow your capability by pursuing and investing in personal development opportunities.

  • Keep up-to-date with emerging developments in the Data Science, ML engineering and MLOps fields, and proactively share findings with the team.

About you

We’re looking for candidates with the following knowledge, experience and capabilities:

  • Computer science fundamentals: a clear understanding of data structures, algorithms, software design, design patterns and core programming concepts.

  • Experience with the core Python data stack (Pandas, NumPy, Scikit-learn, etc) developed in a commercial setting, an appreciation of pipeline orchestration frameworks (e.g., Airflow, Kubeflow Pipelines, etc), applied knowledge of statistical modelling and/or experience in implementing and supporting ML systems.

  • Demonstrable understanding of key concepts including Python testing frameworks, CI/CD, source control, etc.

  • Experience of working with large data sets and with data platforms to deploy scaled Machine Learning models in a live environment.

  • Demonstrable commercial experience across the full software development lifecycle, from experimentation through to live production.

  • Exposure to some GCP cloud tooling (e.g. VertexAI, BigQuery) is highly desirable.

  • Sound understanding of and/ or desire to learn about retail banking and how to apply your technical skills in this area.

About working for us

Our focus is to ensure we are inclusive every day, building an organisation that reflects modern society and celebrates diversity in all its forms. We want our people to feel that they belong and can be their best, regardless of background, identity, or culture. We were one of the first major organisations to set goals on diversity in senior roles, create a menopause health package, and a dedicated Working with Cancer initiative. And it is why we especially welcome applications from under-represented groups. We are disability confident. So, if you would like reasonable adjustments to be made to our recruitment processes, just let us know.

If you are excited by the thought of becoming part of our team, get in touch. 

We would love to hear from you!

At Lloyds Banking Group, we're driven by a clear purpose; to help Britain prosper. Across the Group, our colleagues are focused on making a difference to customers, businesses and communities. With us you'll have a key role to play in shaping the financial services of the future, whilst the scale and reach of our Group means you'll have many opportunities to learn, grow and develop.

We keep your data safe. So, we'll only ever ask you to provide confidential or sensitive information once you have formally been invited along to an interview or accepted a verbal offer to join us which is when we run our background checks.  We'll always explain what we need and why, with any request coming from a trusted Lloyds Banking Group person. 

We're focused on creating a values-led culture and are committed to building a workforce which reflects the diversity of the customers and communities we serve. Together we’re building a truly inclusive workplace where all of our colleagues have the opportunity to make a real difference.