Join us as a Lead Machine Learning Engineer, Climate

In this role, you will be leading a team of engineers to build innovative, data driven solutions and productionise machine learning models You'll be driving and embedding the deployment, automation, maintenance and monitoring of machine learning models and algorithms Day-to-day, you'll make sure that models and algorithms work effectively in a production environment while promoting data literacy education with business stakeholders If you see opportunities where others see challenges, you'll find that this solutions-driven role will be your chance to solve new problems and enjoy excellent career development What you'll do

As a Lead Machine Learning Engineer, you'll collaborate with colleagues to design and develop cutting-edge machine learning products that power our bank and delight our customers. Leading a team of engineers, you'll be responsible for both technical and people leadership, and overseeing the development, deployment and maintenance of advanced machine learning models and algorithms, including large language models.

You'll also plan, manage, and deliver complex projects, involving a variety of colleagues and teams across our business. In addition, you'll lead direct reports and wider teams in an agile way within multi-disciplinary data and analytics teams to achieve agreed project and Scrum outcomes.

Your responsibilities will include:

Understanding the complex requirements and needs of business stakeholders, developing good relationships and how machine learning solutions can support our business strategy Working with colleagues to productionise machine learning models, including pipeline design and development and testing and deployment, so the original intent is carried over to production Creating frameworks to ensure robust monitoring of machine learning models within a production environment, making sure they deliver quality and performance Understanding and addressing any shortfalls, for instance, through retraining Leading direct reports and wider teams in an Agile way within multi-disciplinary data and analytics teams to achieve agreed project and central enablement outcomes The skills you'll need

To be successful in this role, you'll likely have a good academic background in a STEM discipline, such as Mathematics, Physics, Engineering or Computer Science. You'll have the ability to use data to solve business problems, from hypotheses through to resolution.

We'll look to you to have experience with machine learning on large datasets, as well as experience building, testing, supporting, and deploying advanced machine learning models into a production environment using modern CI/CD tools, including git, GitLab and CodeDeploy. In addition, a good understanding of governance processes involved in deploying and maintaining models in production would be desirable.

You'll also demonstrate:

Expertise in machine learning approaches and algorithms, such as time-series forecasting, classification, regression, large language models, and generative AI Strong programming and scripting skills, particularly in Python Experience with experiment design Knowledge of the financial services industry and the ability to identify wider business impact and risk opportunities Excellent communication and stakeholder management skills with the ability to proactively engage with a wide range of stakeholders Good experience working on cloud, preferably with AWS and Sagemaker Hours 35

Job Posting Closing Date: 11/09/2025

Ways of Working:Remote First #J-18808-Ljbffr