1 to 25 of 92 Permanent Feature Engineering Jobs in England

Score and Ad Account Health. Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and insights that inform model development and optimization. Feature Engineering: Collaborate with data engineers to create and maintain feature engineering pipelines to support model training. Model Evaluation: Implement rigorous evaluation … methodologies to assess model performance, making necessary adjustments for continuous improvement. Deployment and Integration: Work closely with engineering teams to deploy models and integrate them into our products through APIs. Collaboration: Collaborate closely with product managers, full‐stack engineers, and TPMs to ensure seamless integration of data science solutions ...

workflows, and develop containerised model services that integrate directly into the OneView platform. This includes hands‐on work with model architectures, feature engineering, model optimisation, performance debugging, schema‐aligned data preparation, and ML‐driven interfaces. This is a role for engineers who want to build and maintain real … real systems, and solve real operational ML problems – not just prototypes. You will work directly with production data, client technical teams, and our internal engineering ecosystem to deliver AI components that are robust, scalable, and deployed into live environments. Key Responsibilities Machine learning engineering Design, train and optimise ...

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 ...

Principal, AI/ML Engineer leads the design, delivery and continuous improvement of AI and ML solutions within their area of responsibility, aligning engineering activities to the Bank’s broader AI strategy and long-term objectives. The role combines strong technical leadership with a clear focus on delivery outcomes … operates with a clear understanding of the wider technology landscape, contributing to strategic direction while taking accountability for translating this into practical, high-quality engineering outcomes across squads. Leads the definition and execution of AI/ML engineering direction across one or more squads, ensuring alignment with ...

hire has very meaningful impact.They are looking for a Senior Data Scientist to lead the predictive analytics capability and their critical programme.You’ll design feature engineering pipelines, select and validate classification and regression models, and establish rigorous evaluation methodology (targeting AUC-ROC 0.85) across a 300M+ point education … explainable and production-ready.Core Responsibilities: Predictive Model Development : Build and validate supervised learning models (classification & regression) using complex, multi-source, time-series-influenced data. Feature Engineering : Design scalable feature pipelines across attendance, behaviour, wellbeing, assessment and SEND datasets. Evaluation & Methodology : Establish rigorous evaluation frameworks including ...

stakeholders across the business to expand the understanding and impact of machine learning and AI throughout Trainline. We are looking for a Machine Learning Engineering Manager to join our team help shape the future of train travel. You will be part of a highly innovative AI and ML platform … enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of users. As a Machine Learning Engineering Manager at Trainline you will... 🚄 Lead a high performing team of Machine Learning Engineers working alongside Software Engineers, Data Scientists, Data Engineers and Product Managers ...

solutions at scale that drive measurable impact for Trainline Own the full end‐to‐end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance Partner with stakeholders to propose innovative data products that leverage Trainline’s extensive … Flow Have experience with agile delivery methodologies and CI/CD processes and tools Have broad understanding of data extraction, data manipulation and feature engineering techniques Are familiar with statistical methodologies Have great communication skills Nice to have Experience with transport industry and/or geographical information systems ...

building the future of population health management. As a Senior Machine Learning Engineer, you will sit at the intersection of data science, platform engineering, and production systems. Your mission is to design and operate the foundations that allow ML, analytics, and agentic AI systems to move safely and reliably … from experimentation into regulated healthcare production environments on Google Cloud Platform. You will be the primary interface between Data Science and Platform Engineering, enabling rapid iteration while enforcing production and compliance standards. Responsibilities Design and implement Onsera's agentic AI platform – architect LLM/agent framework selection, standardized patterns ...

systems that process high-volume, high-value data and increasingly leverage AI and automation to deliver measurable customer and business outcomes. We value pragmatic engineering, clear thinking, and continuous learning. Our teams are small, autonomous, and outcome-focused, with a strong emphasis on quality, ownership, and collaboration. … platform scalability, operational excellence and maturity, and cost-efficient growth to support our long-term strategy and enterprise ambitions. The Role AI Platform Architecture & Engineering Own the design, build, and evolution of Infinity’s AI platform - the infrastructure layer that underpins AI-driven product capability and AI-assisted engineering ...

data scientists, software engineers, and domain specialists to develop intelligent analytics platforms leveraging modern ML, MLOps, and generative AI technologies within a highly collaborative engineering environment. Key Responsibilities: Design, develop, and deploy production-grade machine learning solutions for predictive analytics and fault detection. Build scalable ML inference services … APIs using Python and C#/.NET. Develop robust data pipelines and feature-engineering workflows across large industrial datasets. Apply signal processing and machine learning techniques to operational data. Implement and optimise model inference pipelines. Develop and maintain containerised ML workloads using Docker and cloud-native tooling. Collaborate ...

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 ...

features, model selection, architecture decisions Conduct exploratory data analysis and communicate insights Collaborate with data engineers, architects, and business analysts on integrated solutions Build feature engineering pipelines and automated data preparation workflows Design AI solutions for commercial transformation including pricing optimization, customer segmentation, and revenue management Develop scalable … proposals and technical assessments for new opportunities and internal knowledge transfer Essential Qualifications Degree or equivalent certification in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field Proven experience building and implementing LLM-based solutions (GPT, Claude, Llama, Mistral, or similar) Hands‐on experience with at least ...

model selection, and architecture decisions Conduct exploratory data analysis and communicate insights Collaborate with data engineers, architects, and business analysts on integrated solutions Build feature‐engineering pipelines and automated data preparation workflows Design AI solutions for commercial transformation including pricing optimization, customer segmentation, and revenue management Develop scalable … proposals and technical assessments for new opportunities and internal knowledge transfer Essential Qualifications Degree or equivalent certification in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field Proven experience building and implementing LLM‐based solutions (GPT, Claude, Llama, Mistral, or similar) Hands‐on experience with at least ...

solutions and regulatory reporting — ensuring teams across the business can trust and use data with confidence. You’ll collaborate closely with colleagues in Data Engineering, Data Science, Pricing, Platform Engineering and MLOps, acting as a trusted partner and technical authority. Together, you’ll define clear standards … self‐service analytics and AI/ML model consumption. Collaborate with ML Ops and Data Science teams to define data product standards and feature engineering patterns. Evaluate and lead adoption of emerging Azure and Databricks capabilities — including Microsoft Fabric, OneLake and DirectLake — where they advance the data architecture. ...

solutions and regulatory reporting — ensuring teams across the business can trust and use data with confidence. You’ll collaborate closely with colleagues in Data Engineering, Data Science, Pricing, Platform Engineering and MLOps, acting as a trusted partner and technical authority. Together, you’ll define clear standards … self‐service analytics and AI/ML model consumption. Collaborate with ML Ops and Data Science teams to define data product standards and feature engineering patterns. Evaluate and lead adoption of emerging Azure and Databricks capabilities — including Microsoft Fabric, OneLake and DirectLake — where they advance the data architecture. ...

exploration into advanced techniques, including LLMs, RAG architectures, and Generative AI applications to create new forms of automated analysis and augmented intelligence products. Production Engineering & MLOps : Translate validated prototypes into robust, production‐ready specifications, and lead the implementation of MLOps best practices (CI/CD, monitoring, serving) required … reliable deployment of models. Complex Data & Feature Engineering : Deeply explore complex, multi‐modal data (e.g., high‐dimensional data, text, time series) defining the necessary features and data pipelines to support highly accurate experimental models for strategic analysis. Cross‐Functional Collaboration : Work closely with the Product Manager, Data Scientists ...

scalable, production-ready solutions across airline operations. 🔹 Role Responsibilities • Design and deploy predictive & prescriptive AI/ML models • Perform exploratory data analysis and advanced feature engineering • Collaborate closely with Data Engineering teams for model-ready datasets • Translate analytical insights into business impact and operational improvements • Continuously optimize ...

priorities. Identify high-value ML use cases and translate commercial problems into scalable analytical solutions. Lead end-to-end model lifecycle delivery: problem framing, feature engineering, experimentation, validation, deployment, monitoring, and iteration. Establish best practices for experimentation, evaluation, reproducibility, and documentation. Set standards for model governance, explainability, monitoring … financial environment. Machine Learning & Delivery Architect and develop robust ML models (e.g., classification, regression, anomaly detection) using Python and cloud-based tooling. Design scalable feature pipelines in collaboration with Data Engineering. Lead productionisation efforts, including pipeline design, model versioning, and monitoring frameworks. Implement safe deployment strategies (e.g., champion/ ...

This is a senior individual contributor role with strong influence through mentorship, collaboration, and technical leadership. You will work closely with partners across product, engineering, and the business to design and deliver data-driven solutions. We welcome candidates from a range of backgrounds and experiences who are excited … Development Lead by example through hands‐on coding and model development. Design, prototype, and validate innovative solutions for high‐impact problems. Partner with engineering teams to deploy models into production environments. Domain Expertise Leverage deep knowledge of aviation, travel, or related industries to inform modelling approaches and deliver customer ...

Company Ion recruitment Location Surrey, UK (Office based) Overview A global software company is evolving its core engineering platforms by embedding machine learning and applied AI into high‐performance simulation and modelling tools used worldwide. This is a hands‐on applied AI role — focused on building and deploying … solutions inside production‐grade engineering systems, not isolated research or experimental prototypes. Responsibilities Create, deploy, and maintain machine learning models in production engineering software systems. Own the full ML pipeline: data preparation, feature engineering, training, evaluation, and optimisation. Translate complex scientific/engineering problems into ...

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 ...

Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. … with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across ...

Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. … with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across ...

Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. … with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across ...

Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. … with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across ...