Lead Machine Learning Engineer

Join us as a Lead Machine Learning Engineer

·         Join us in this exciting role and help shape the future of AI and machine learning at our bank

·         You’ll be at the forefront of applied AI and AI research in the financial services industry, leading a team of talented data engineers to build innovative, data-driven solutions and productionise machine learning models

·         With a focus on attracting top talent, you'll play a key role in recruitment, team growth, and representing the bank at internal and external events

·         If you're passionate about pushing the boundaries of AI and machine learning, this is your chance to make a significant impact and enjoy excellent career development opportunities

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:

·         Working closely with stakeholders to identify opportunities for AI-driven solutions, while promoting data literacy and fostering a culture of innovation within the bank

·         Understanding the complex requirements and needs of business stakeholders, developing strong relationships, and identifying how AI and machine learning solutions can support our business strategy

·         Productionising machine learning models, including pipeline design, development, testing, and deployment, ensuring the original intent is carried over to production

·         Creating frameworks for robust monitoring of machine learning models within a production environment, ensuring they deliver quality and performance

·         Addressing any shortfalls, such as through retraining, and staying up to date with the latest AI research and technologies

The skills you'll need

To be successful in this role, you’ll have a passion for staying current with AI research and a desire to contribute to the field. You’ll come with a strong academic background in a STEM discipline, such as Mathematics, Physics, Engineering, or Computer Science, ideally with an MSc or a PhD qualification. You'll also have a proven track record of using data to solve business problems and experience with machine learning on large datasets.

In addition, you’ll need experience of building, testing, supporting, and deploying advanced machine learning models into a production environment using modern CI/CD tools, including Git, AWS, AWS Sagemaker, Docker, Terraform, Cloud Formation, Kubernetes, PyTorch, TensorFlow, Jax, Numpy, Scikit-learn, and more. Experience of working in a matrix organisation will be advantageous.

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