Barclays
MachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Machine Learning Engineer at Barclays. Skills: Machine learning development, Python programming, Distributed data processing, Deep learning, NLP, Software engineering, MLOps, LLMOps, Stakeholder management. Design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making. Design analytics and modelling solutions to complex business problems using domain expertise”
Industry & Context.
Solve complex business problems; Sophisticated analytical thought; In-depth analysis with interpretative thinking; Define problems; Adopt and include the outcomes of extensive research in problem solving processes
Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy, Ensure all development activities are undertaken within the defined control environment, Adherence to strict governance, documentation, and regulatory standards
What They're Looking For.
Must 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
Nice to Have
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
What You'll Do.
and support mathematical
and machine learning models and analytics used in business decision-making
Design analytics and modelling solutions to complex business problems using domain expertise
Develop high performing
comprehensively documented analytics and modelling solutions
Implement analytics and models in accurate
Provide ongoing support for the continued effectiveness of analytics and modelling solutions
Design and build advanced machine learning and AI solutions
Develop scalable ML pipelines
Develop agentic AI systems
Develop production-grade model code
Develop robust monitoring systems
Play a key role across the full machine learning lifecycle—from initial concept and data exploration through to deployment
How You'll Work.
Team & Collaboration
Collaboration with technology to specify any dependencies required for analytical solutions; Demonstrate efficacy of solutions to business users and independent validation teams; Work with technology to operationalise analytics and models; Working closely with data scientists and engineers; Collaborate with other areas of work, for business aligned support areas; Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders; Guide team members through structured assignments; Identify the need for the inclusion of other areas of specialisation to complete assignments
Communication Scope
Demonstrating efficacy to business users; Advise key stakeholders, including functional leadership teams and senior management
Process & Methodology
Plan resources, Manage budgets, Manage and maintain policies, Deliver continuous improvements, Lead collaborative, multi-year assignments
Full Job Description
# **Job Description** **Purpose of the role** To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making **Accountabilities** * Design analytics and modelling solutions to complex business problems using domain expertise. * Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools. * Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams. * Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them. * Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users. * Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy. * Ensure all development activities are undertaken within the defined control environment. **Vice President Expectations** * To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures.. * If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements.. * If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thr
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