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Date live:
Jun. 01, 2026
Business Area:
Group Economic Crime COO
Area of Expertise:
Risk and Quantitative Analytics
Reference Code:
JR-0000098991
Contract:
Permanent
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Explore locationWe are seeking a highly skilled Machine Learning Engineer to design and build advanced machine learning and AI solutions that enhance our ability to detect financial crime, prevent fraud, and safeguard our customers.
Working closely with data scientists and engineers, you will focus on developing scalable ML pipelines, agentic AI systems, production-grade model code, and robust monitoring systems. You will play a key role across the full machine learning lifecycle—from initial concept and data exploration through to deployment—while ensuring adherence to strict governance, documentation, and regulatory standards.
To be successful as a Machine Learning Engineer, you should have:
Extensive experience in machine learning development (training and/or deploying models at scale).
Outstanding programming skills in Python.
Experience with distributed data processing frameworks (e.g., Spark).
Experience with deep learning/NLP frameworks (e.g., PyTorch, Hugging Face).
Solid understanding of software engineering principles and ML lifecycle practices (MLOps/LLMOps).
Previous experience of owning and delivering ML projects, including stakeholder management.
Some other highly valued skills may include:
Experience leading machine learning engineering or development teams.
Experience with LLMs and agentic AI systems, including relevant frameworks (e.g., Agents SDK, Anthropic SDK, AWS Bedrock, LangGraph, CrewAI).
Experience with cloud platforms (AWS, Azure, GCP) or ML platforms (e.g., Databricks).
Exposure to fraud detection, anti-money laundering, anomaly detection, or graph/network-based modelling.
Understanding of model risk management, governance, and regulatory controls in financial services.
You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.
This role will be located at our Glasgow office.
Purpose of the role
To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making
Accountabilities
Vice President Expectations
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.