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# AI/ML Engineer

- **Company:** Capgemini
- **Location:** Slough, UK (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Data Cleansing, Information Engineering, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, NumPy, Tensorflow, SQL Databases, Google Cloud, Feature Engineering, Pytorch, Large Language Models, Generative AI, Pandas, Scikit Learn, Xgboost, Data Management, Machine Learning Operations
- **Published:** June 15, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/x/39038958/

## About the Role

We are a Disability Confident Employer:Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government's Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:Declare they have a disability, andMeet the minimum essential criteria for the role.Please opt in during the application process.

## Description

AI/ML Engineer / Senior Machine Learning Engineer Experience: 5-10 yearsClient Domain: Banking / Financial ServicesLocation: As per client requirement / Hybrid
About the Job you are considering:We are hiring an experienced AI/ML Engineer to design, develop, and deploy scalable machine learning and Generative AI solutions for banking and financial services. The role involves building end-to-end ML pipelines, deploying models into production, and ensuring performance, reliability, and regulatory compliance.
Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
Your Role:Develop and deploy ML models for use cases like fraud detection, risk modeling, and customer analyticsBuild predictive, classification, clustering, and recommendation modelsPerform data preprocessing, feature engineering, and model evaluationDesign scalable ML pipelines and production-grade solutionsDevelop NLP and GenAI solutions (RAG, embeddings, LLM-based applications)Deploy models using APIs, containers, and cloud platformsMonitor model performance, drift, and reliabilityCollaborate with cross-functional teams and stakeholdersEnsure compliance with banking regulations and security standards
Your Skills:Strong Python programmingExpertise in ML algorithms and statistical modelingHands-on experience with Scikit-learn, Pandas, NumPy, XGBoost/LightGBMExperience with TensorFlow / PyTorch / KerasSolid understanding of feature engineering, model tuning, and evaluation metricsExperience with SQL and data handlingKnowledge of MLOps (CI/CD, model deployment, monitoring)Experience deploying ML models in productionGood communication and problem-solving skills
Good-to-Have SkillsExperience in banking domain (fraud detection, credit risk, AML, churn)Knowledge of Generative AI, LLMs, RAG, and prompt engineeringFamiliarity with vector databases (FAISS, Pinecone, etc.)Experience with LangChain, LlamaIndex, or similar frameworksExposure to cloud platforms (Azure, AWS, GCP)Understanding of data engineering and big data tools


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