Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Machine Learning Engineer

Barclays
Glasgow
2 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer (GenAI Algos)

Senior Machine Learning Engineer (GenAI Algos)

Senior Machine Learning Engineer (GenAI Algos)

Senior Machine Learning Engineer (GenAI Algos)

Overview

Barclays Glasgow, Scotland, United Kingdom

2 days ago Be among the first 25 applicants

Join our innovative AI/ML team at Barclays Corporate Bank as a Senior Machine Learning Engineer, where we bridge the gap between cutting-edge data science exploration and real-world business application integration. We manage internal cloud platforms that support exploratory data science work while specialising in transforming conceptual ML models into production-ready applications that drive critical business decisions and processes. As part of Barclays' strategic AI/ML initiative, our team plays a vital role in establishing the corporate bank as a leader in financial data analytics innovation. We offer the opportunity to work with enterprise-scale data using cloud technologies, implement MLOps best practices, and collaborate with talented data scientists to deliver solutions that create measurable business impact across the organization.

To be successful in this role, you will need the following:



  • Strong proficiency and experience in AWS based Machine Learning technologies (AWS SageMaker, Lambda, S3, EC2).
  • Experience with CI/CD pipelines and Docker containerisation for ML model development/deployment.
  • Data preprocessing and feature engineering expertise.
  • Programming skills in Python and ML frameworks (TensorFlow, Torch, scikit-learn).
  • Statistical analysis and model evaluation capabilities.
  • Previous experience in the banking sector is mandatory.

Some Other Highly Valued Skills May Include



  • Experience with experiment tracking and model registry tools (MLflow, DVC).
  • Knowledge of infrastructure as code (Terraform, CloudFormation).
  • Familiarity with data visualisation tools and techniques.
  • Advanced knowledge of ML algorithms and their optimisation.
  • Experience with distributed computing for large-scale ML workloads (Spark).
  • Experience with pricing models or pricing-related projects is strongly preferred.
  • Additional Experience in GenAI projects implementation (multiple RAG patterns, prompt management, agentic workflows) is preferred.

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.


The successful candidate will be based in Glasgow.


Purpose of the role

To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.


Accountabilities

  • Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
  • Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
  • Development of processing and analysis algorithms fit for the intended data complexity and volumes.
  • Collaboration with data scientist to build and deploy machine learning models.

Vice President Expectations

  • 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.
  • Be a subject matter expert within own discipline and will guide technical direction. Lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. Train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions.
  • Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
  • Manage and mitigate risks through assessment, in support of the control and governance agenda.
  • Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
  • Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
  • Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
  • Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
  • Adopt and include the outcomes of extensive research in problem solving processes.
  • Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.

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.


Seniority level

  • Mid-Senior level

Employment type

  • Full-time

Job function

  • Engineering and Information Technology

Industries

  • Banking and Financial Services

Referrals increase your chances of interviewing at Barclays by 2x


Get notified about new Senior Machine Learning Engineer jobs in Glasgow, Scotland, United Kingdom.


We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.