Senior Machine Learning Engineer

Lloyds Banking Group

. Build and maintain machine learning solutions in production across the Consumer business within Lloyds Banking Group .

Posted 9/24/2026full-timeBristol • United KingdomSenior💰 £72,702 - £80,780 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining machine learning solutions using Python, with a strong focus on cloud services, data governance, and risk management. Proven ability to lead technical projects from experimentation to production while adhering to engineering standards and collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Python Machine Learning LibrariesCloud Services DevelopmentMachine Learning Operations ToolingInfrastructure as CodeRetail Banking Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningSoftware Engineering Best PracticesAutomated TestingContinuous IntegrationContinuous DeliveryProduction DeploymentsData Stores and ArchitecturesLarge Datasets ManagementApplication Programming InterfaceGenerative Artificial Intelligence

Soft Skills

Technical LeadershipCollaborationInfluencing Decision-MakingKnowledge SharingIncident Management

Tools & Technologies

PandasScikit-learnXGBoostVertex AIBigQueryCloud RunKubeflow PipelinesDbtTerraformKubernetes

Industry Keywords

Machine Learning SolutionsData ScienceModel GovernanceRisk ManagementRetail Banking

Tech Stack

Tools & technologies

BigQueryCloudKubernetesPandasPythonScikit-LearnTerraform

About the role

Key responsibilities & impact

Build and maintain machine learning solutions in production across the Consumer business within Lloyds Banking Group
Develop and maintain machine learning systems in Python alongside data scientists and other machine learning engineers
Take projects from experimentation through to production
Design and integrate solutions with continuous integration and continuous delivery tools, application programming interfaces, and Dynatrace
Engage with business and technical collaborators to understand requirements and influence decision-making
Propose, evaluate and advocate for technology, platform and architecture choices in line with Lloyds Banking Group guidelines
Drive engineering standards, consistency and culture through technical leadership and knowledge sharing
Lead incident management and resolution with the strategic platform team and business partners
Identify opportunities to improve solutions and present clear delivery plans
Deliver results aligned with data science, model governance, and risk management policies and procedures
Build relationships with specialized colleagues across data science, governance and risk management

Requirements

What you’ll need

Advanced understanding of software engineering best practice, programming concepts, automated testing, continuous integration and continuous delivery, and production deployments
Commercial experience using Python machine learning libraries, such as Pandas, Scikit-learn and XGBoost
Proven development experience with cloud services, data stores and architectures, such as Vertex AI, BigQuery and Cloud Run
Hands-on experience with machine learning operations tooling and frameworks for large datasets, such as Kubeflow Pipelines and dbt
Understanding of production monitoring
Experience with Infrastructure as Code, including Terraform and Kubernetes
Experience with application programming interface authentication flows and networking
Experience collaborating with central platform, architecture and governance teams to move solutions into live production
Experience across the full software development lifecycle, from experimentation through to live production
Sound understanding of retail banking, or desire to learn how to apply technical skills in this area
Exposure to generative artificial intelligence and agentic tooling, such as Agent Development Kit or LangChain
Experience configuring large language models to optimise cost and benefit

Benefits

Comp & perks

Flexible working options
Job share
Pension contribution of up to 15%
Annual performance-related bonus
Share schemes including free shares
Benefits adaptable to lifestyle, such as discounted shopping
30 days’ holiday, with bank holidays on top
Wellbeing initiatives
Generous parental leave policies
Workplace adjustments for colleagues with disabilities
Reasonable adjustments throughout the recruitment process
Career progression and personal and professional development support
Disability Confident Scheme interview guarantee for eligible applicants