23 of 23 Permanent Feature Engineering Jobs in England

models by converting analysts' Python code into scalable, maintainable and deployable workflows Design, build and maintain data pipelines for pricing inputs, including ingestion, transformation, feature preparation and quality checks Build and automate workflows for elasticity, forecasting, optimisation and other pricing models Develop and manage API integrations, including competitor pricing … feeds and downstream systems Work closely with pricing analysts to translate pricing logic into production-ready processes Support model performance improvement through data preparation, feature engineering and data mining techniques Monitor production processes and model performance over time, recommending corrective action where required Ensure pricing models are deployed ...

taxonomies, citations, metadata, and content from every scientific discipline. Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI. Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization … inference, experimentation, monitoring, and continuous improvement. Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems. Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical ...

years to come. AI at the Core: This is a true AI/Data-driven product. ML isn't a nice-to-have feature - it's the product. Your infrastructure directly enables business value. Truly Cross-functional: the Global:IQ team is a tight collaboration between technical and commercial … areas. Measures of success In the first few months, you would have: Defined a clear operating model between Data Engineering/MLOps and teams responsible for model development. Onboarded key 1st and 3rd party datasets following existing ingestion patterns/standards. Delivered an initial end-to-end MLOps path ...

technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that our models are scalable, secure, explainable, and governed to enterprise‐grade standards. You will contribute … compliance framework. This is a highly hands‐on, highly technical, principal‐level role that combines architectural vision with deep practical expertise in ML engineering and AWS-native MLOps. Key Responsibilities Technical Leadership & Architecture Define the end‐to‐end ML architecture for the matching platform, including data pipelines, model training ...

position responsible for designing, building, and deploying enterprise-grade AI solutions that drive measurable business value across the organisation. Working closely with IT, Data, Engineering, and senior business stakeholders, you will lead the development and implementation of advanced AI solutions, leveraging Large Language Models (LLMs), Retrieval-Augmented Generation … expertise with strategic thinking, taking solutions from concept through to production deployment and adoption. The ideal candidate will have a strong foundation in AI Engineering combined with a robust Data Science background, enabling them to develop, evaluate, and optimise AI solutions that deliver measurable business outcomes. This role would ...

understanding of JDBC and database internals. Experience with CI/CD pipelines and Distributed and Concurrent Systems Experience with machine learning basics (data pipelines, feature engineering, recall/precision, familiarity with machine learning systems in production) is a huge plus A strong product mindset and passion for user … work – a practical guide DEI @ Wise Wise Tech Stack (2025 update) See what it's like to work at Wise London! Our Engineering career map Wise Engineering – https://medium.com/wise-engineering What do we offer: Starting salary: £87,500 - £111,000 + RSUs Wise ...

home 100% of the time. Your Role: Implement and finetune generative AI models under the guidance of senior team members Contribute to prompt engineering and development of Ai powered workflows Assist with the deployment monitoring and maintenance of AI models in production environments Collaborate with data scientists and engineers … ensure seamless integration of AI capabilities Perform data preprocessing feature engineering and API development for AI applications Participate in code reviews testing and documentation to ensure quality and reliability Stay updated with advancements in GenAI and share relevant learnings with the team Required Technical Skills Handson experience with ...

security platform, contributing to innovative features that leverage advanced analytics, behavioural detection, and intelligent threat prevention. Working as part of a highly collaborative engineering team, you will help bridge the gap between cutting-edge machine learning research and production-grade security software. To see what our engineering teams … design and implementation of intelligent threat detection, behavioural analysis, and anomaly detection capabilities. Participate in architecture discussions, code reviews, testing, and continuous improvement of engineering practices. Evaluate emerging AI technologies and contribute to future product innovation. Requirements for the C++ AI/ML Software Engineer Strong proficiency in modern ...

Join our global Quantitative Trading & Research (QTR) team, where you’ll apply your expertise in Derivatives Modelling, Financial Engineering, Data Science, and Quantitative Development. As part of JP Morgan’s leading QTR Group, you’ll innovate with unique analytics and mathematical models, enhancing business practices through automation. We develop … limitations, and model performance. Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/method reviews, establish research engineering best ...

queries and manage remediation actions and findings Your skills and experience Advanced degree (Master’s or PhD) in a quantitative discipline (e.g., Mathematics, Physics, Engineering, Computer Science) 7+ years’ experience developing analytical or machine learning models in financial services (ideally Anti-Financial Crime/Screening) Experience building Natural Language … Processing (NLP)/Machine Learning (ML)/Artificial Intelligence (AI) pipelines, including feature engineering, model training, evaluation and monitoring Experience designing evaluation frameworks for LLM use cases (e.g., human-in-the-loop, calibration, guardrails, auditability) Experience with hyperparameter tuning at scale and experimentation frameworks Strong technical experience with ...

logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling ...

limitations, and model performance. Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/method reviews, establish research engineering best … resourcing via data‐driven analysis, scenario studies, and clear articulation of trade‐offs. Lead development of ML/AI solutions end‐to‐end (feature engineering, model training/validation, MLOps, monitoring and drift management) with rigorous controls, documented governance, and demonstrable business value. Uphold standards for documentation, reproducibility ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

ownership and production-grade model deployment. The Role As Senior Data Scientist, you will: Own end-to-end ML solutions -from problem framing and feature engineering to deployment, monitoring, and governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models … using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift, and retraining Drive clear documentation, traceability, and governance appropriate for a regulated environment This role requires someone ...

optimization techniques for LLM-based agents Resource-constrained AI model deployment Vector databases and semantic search (e.g., Pinecone, Weaviate, Milvus, Qdrant , and ChromaDB ) Prompt engineering for efficient agent reasoning LLM fine-tuning and instruction optimization Graph databases for network topology and context management Feature engineering for network … deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion. Make it real | www.capgemini.com ...

that reflect risk assessment outcomes and model performance. Qualifications A bit about you: Proven track record of deploying models from scratch, including data preprocessing, feature engineering, model selection, evaluation, and monitoring. Strong Python knowledge. Ability to read through code, especially Java. Demonstrable experience collaborating with engineering ...

using Python, TensorFlow, PyTorch Work on supervised, unsupervised, and reinforcement learning problems Clean and process large datasets to extract insights and train algorithms Perform feature engineering to improve model accuracy Design ML pipelines and automate model deployment Collaborate with software engineers to integrate models into applications Use MLOps ...

build scalable forecasting systems that continuously generate, deploy and improve predictive models. You'll work with large-scale data, applying machine learning, experimentation and feature engineering to improve prediction accuracy and drive better customer outcomes. You'll also help shape product strategy, establish data science best practices ...

into data, surface anomalies, communicate findings frequently, and drive actions across teams. Good to have FinTech/payments and Fraud experience. Experience with feature engineering and model monitoring. Familiarity with Airflow/DBT/Git/Snowflake and production data platforms. If you care about protecting customers ...

SeniorAIEngineerManchester Agrowingtechnology-ledbusinessisseekinga SeniorAIEngineer toplayapivotalroleinshapinganddeliveringitsAIstrategy.Thisisasenior-level,hands-onpositionresponsiblefordesigning,building,anddeployingenterprise-gradeAIsolutionsthatdrivemeasurablebusinessvalueacrosstheorganisation. WorkingcloselywithIT,Data,Engineering,andseniorbusinessstakeholders,youwillleadthedevelopmentandimplementationofadvancedAIsolutions,leveragingLargeLanguageModels(LLMs),Retrieval-AugmentedGeneration(RAG),AIAgents,MachineLearning,andAzureAIservices.Youwillprovidetechnicalleadership,establishbestpractices,andhelpbuildtheorganisationslong-termAIcapability. ThebusinessisinvestingheavilyinAIandislookingforsomeonewhocancombinedeeptechnicalexpertisewithstrategicthinking,takingsolutionsfromconceptthroughtoproductiondeploymentandadoption. TheidealcandidatewillhaveastrongfoundationinAIEngineeringcombinedwitharobustDataSciencebackground,enablingthemtodevelop,evaluate,andoptimiseAIsolutionsthatdelivermeasurablebusinessoutcomes. ThisrolewouldsuitanexperiencedAIprofessionalwhoenjoyssolvingcomplexbusinesschallenges,mentoringothers,influencingtechnicaldirection,anddeliveringinnovativeAIsolutionsatscale. RolePurpose AsaSeniorAIEngineer,youwillleadthedesign,development,deployment,andoptimisationofenterpriseAIsolutions,ensuringtheyaresecure,scalable,maintainable,andalignedtobusinessobjectives. YouwillactasasubjectmatterexpertforAItechnologies,helpingtodefinearchitecture … Strongunderstandingofenterprisecloudarchitecture,includingVNets,EntraID,APIGateways,networking,andsecureintegrations. ExperiencedeployingandmanagingAIworkloadswithinproductionenvironments. StrongSQLanddataengineeringskills,workingwithbothstructuredandunstructureddatasets. AbilitytotranslatecomplexdatasetsintoactionableinsightsandAI-drivenbusinesssolutions. ExperienceimplementingAIgovernance,security,monitoring,andoperationalbestpractices. Excellentcommunication,leadership,stakeholdermanagement,andproblem-solvingskills. HighlyDesirable StrongDataSciencebackground,withexperienceinstatisticalmodelling,predictiveanalytics,featureengineering,experimentation,andmodelevaluation. ExperienceapplyingDataSciencemethodologiestosolvecomplexbusinessproblemsandidentifyopportunitiesforAIadoption. ExperiencewithGenAIOps,LLMOps,MLOps,andAIobservabilityplatforms. ExposuretoComputerVision,OCR,VoiceAI,ConversationalAI,ormultimodalAIsolutions. Experienceworkingwithinoperational,retail,automotive,logistics,orcustomer-centricorganisations. KnowledgeofResponsibleAI,AIgovernanceframeworks,andregulatoryconsiderations. PreviousexperienceleadingAIinitiatives,mentoringengineers,orhelpingdefineAIstrategyandroadmap. ExperiencebuildingorcontributingtoanAICentreofExcellenceorinternalAIcapabilityfunction. ...