Lead Machine Learning Engineer

WORKING PATTERN: Our work style is hybrid, which involves spending at least two days per week, or 40% of our time, at one of our office sites Here at Lloyds Banking Group, we put our customers at the heart of everything we do, and every colleague has an important part to play. Data Science and Artificial Intelligence form a key part of our strategy, and as a lead Machine Learning Engineer you will be contributing the largest ever transformation in this history of financial services. With 30 million + customers, millions of transactions and 70 thousand colleagues, we have some of the largest datasets in the UK. This combined with our focus in areas such as Gen AI and AI Ethics mean you'll be working at the forefront of Data Science in the banking industry. Want to hear more? The successful candidate for this role will lead the Machine Learning Engineering function within our Data Science & AI Centre of Excellence. The CoE works with Business Units and Group functions across LBG to drive its continued use and adoption of Data science and AI (including GenAI). This is a key technical leadership role within the team - responsible for defining and delivering best practice MLE patterns within our Enterprise ML platform on Google Cloud. As a Lead Machine Learning Engineer, you'll perform the following activities:

• Use expert knowledge of key software development best practices and Python testing frameworks, CI/CD and source control to lead the development of end-to-end machine learning systems in Python
• Use awareness of the latest industry developments to shape the strategy of Machine Learning Engineering at LBG
• Act as a point of technical expertise for data science and AI practitioners across the Group
• Lead, coach and mentor a team of Machine Learning Engineers, taking ownership for the quality of outputs and providing guidance in solving the most complex problems.
• Collaborate with teams across the data and technology job families to help drive the Data Science agenda
• Communicate with business stakeholders to explain technical concepts in meaningful ways, helping to demonstrate the value of Data Science and how to can be used to benefit the organisation
  
  We're keen to speak with candidates who have demonstrable experience in data science, machine learning or software engineering as well as experience in leading technical delivery, managing stakeholders and influencing at senior levels. In particular, candidates with:
• Machine Learning Engineering- The ability to apply ML specific design patterns and work with dedicated ML service/infrastructure, to develop resilient and scalable ML systems with reproducible outputs. This includes ML pipeline composition and orchestration, data and model versioning, backtesting and model monitoring.
• Python- A good understanding of Python including how to write modular Pythonic code, familiarity with the core Python data structures and fluency with pandas; a familiarity with unit testing.
• Software Engineering- The ability to apply software engineering best practices to deploy ML models into production reliably and efficiently, following the principle of test driven development. This requires use of a CICD toolkit and the ability to automate ML pipelines with robust test coverage and monitoring.
• Cloud Technologies- The ability to work with Cloud Technologies efficiently (e.g. Google Cloud Platform), which include a variety of services including storage, compute engine, VPC, Kubernetes, AI services and APIs, for data collection, exploration, visualisation and modelling. Experience of GCP services and VertexAI is advantageous, as is an understanding of infrastructure as code.
We're particularly keen to hear from individuals who have a track record of delivering data science/ machine learning projects within commercial environments. For example, those with experience of having successfully industrialised and delivered data science solutions for large scale industry applications Other Key Skills
• Agile Delivery
• Data Privacy, Ethics & Security
• ML/AI Risk & Governance
• Machine Learning
• Deep Learning
• Statistics & Advanced Analytics
  
  SALARY: £86,900pa to £125,000pa (Dependant on depth of experience and location) plus the benefits listed below, Our focus is to ensure we're inclusive every day, building an organisation that reflects modern society and celebrates diversity in all its forms. We're committed to creating a consciously inclusive workplace where our colleagues can be themselves, thrive and perform at their best. 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. As an inclusive employer, we offer Workplace Adjustments for colleagues with a disability (which may include long-term health and neurodivergent conditions) where it is reasonable to do so. This could include flexibility with regards to office attendance, location, and working pattern.
We are proud to be a Disability Confident Leader. If you have a disability, you can also apply via our Disability Confident Scheme (DCS). Through the DCS, we guarantee to interview a fair and proportionate number of applicants with a disability, whose application meets the minimum criteria for the advertised job role. We also provide adjustments that are reasonable throughout the recruitment process to reduce or remove barriers for applicants with a disability, long-term health condition or neurodivergent condition. If you'd like an adjustment to the recruitment process just let us know We also offer a wide-ranging benefits package, which includes:
• A generous pension contribution of up to 15%
• An annual performance-related bonus
• Share schemes including free shares
• Benefits you can adapt to your lifestyle, such as discounted shopping
• 30 days' holiday, with bank holidays on top
• A range of wellbeing initiatives and generous parental leave policies
If you're excited by the thought of becoming part of our team, get in touch. We'd love to hear from you!