Senior Machine Learning & AI Engineer - Consumer Data Science

Experteer Overview In this role you will design and deliver production-grade ML and AI solutions for Lloyds Banking Group's consumer lending business. You will work with data scientists, engineers and stakeholders to take ideas from experimentation to live production, deploying scalable, secure AI applications in the cloud. You will influence engineering standards and collaborate across platform, governance and business teams to drive value and responsible AI deployment. This is a hands-on role with impact on customers and the bank's digital capabilities. Pay / Benefits

• Deliver ML/AI solutions from experimentation to live production in a cross-functional team Develop and maintain Python ML applications; integrate with cloud platforms, APIs, CI/CD and monitoring tools Influence technical decisions and shape standards, architecture and culture of the team Collaborate with platform, architecture, governance and business teams to deliver secure, scalable, well-governed solutions Contribute to incident management, continuous improvement and future AI engineering direction Tasks 5+ years of experience delivering software across the full development lifecycle Advanced software engineering skills: design patterns, programming concepts, automated testing, CI/CD, production deployments Strong Python experience with Pandas, Scikit-Learn, XGBoost Experience with cloud-based ML/data platforms (e.g., Vertex AI, BigQuery, Cloud Run) Hands-on MLOps tooling (Kubeflow Pipelines, dbt or similar); monitoring large-scale models IaC, Kubernetes, API authentication and distributed systems in enterprise environments Key requirements pension contribution up to 15% annual performance-related bonus share schemes including free shares discounted shopping benefits 30 days' holiday plus bank holidays wellbeing initiatives and parental leave policies
  
  _ Contribute to incident management, continuous improvement and future AI engineering direction Tasks 5+ years of experience delivering software across the full development lifecycle Advanced software engineering skills: design patterns, programming concepts, automated testing, CI/CD, production deployments Strong Python experience with Pandas, Scikit-Learn, XGBoost Experience with cloud-based ML/data platforms (e.g., Vertex AI, BigQuery, Cloud Run) Hands-on MLOps tooling (Kubeflow Pipelines, dbt or similar); monitoring large-scale models IaC, Kubernetes, API authentication and distributed systems in enterprise environments Key requirements pension contribution up to 15% annual performance-related bonus share schemes including free shares discounted shopping benefits 30 days' holiday plus bank holidays wellbeing initiatives and parental leave policies