21 of 21 Permanent Feature Engineering Jobs in England

working across the full ML lifecycle—from design through to production—in a modern, AWS-based environment. You'll be part of an engineering and data team tackling projects like LLM development, intelligent automation, semantic search, and recommendation systems. There's real scope here to influence how MLOps … doing: Building and deploying ML models and LLM applications Fine-tuning large language models for specific use cases Working with prompt engineering and RAG systems Creating end-to-end ML pipelines—ingestion, feature engineering, deployment Developing LLM-powered tools: chatbots, automation, content generation Implementing MLOps practices: versioning ...

engineers and data scientists to design, build, and scale machine learning systems that deliver real business value. Reporting to the Executive Director of ML Engineering, you'll gain hands-on experience developing production-grade pipelines, monitoring frameworks, and scalable ML applications that support mission-critical business functions. This … high-growth opportunity for someone with early industry experience (or strong academic grounding) in machine learning engineering, eager to deepen their expertise in production systems and MLOps while growing within a dynamic AI team operating at the frontier of applied ML. Key Responsibilities: Contribute to the design, development ...

performance, and retrain models as needed. You’ll bring a passion for building reliable ML infrastructure, a strong technical foundation in modern machine learning engineering, and a track record of working in environments where reliability and scale are paramount. Our Data & Analytics team has grown significantly over the last … monitoring, and retraining at scale. Working with data scientists to take models from development to production-grade systems, ensuring scalability, reproducibility, and robustness. Automating feature engineering and data pipeline processes, ensuring reproducibility and auditability. Implementing monitoring and observability to detect drift, bias, and performance degradation, and setting ...

Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic … Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including ...

real AI projects, learning from experts, and gaining hands-on experience with modern AI tools, models, and data pipelines. Whether you studied Computer Science, Engineering, Maths, Data Science, or a related field, if you have a passion for AI and a hunger to learn — we want to hear from … TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model accuracy and efficiency. Deploy & Monitor Models : Learn how to deploy models into production environments and monitor their performance ...

online evals), ensuring factuality, privacy, and cost/performance balance. You will develop and ship models and services hands-on in Python (data prep, feature engineering, training/inference, APIs); write high-quality, tested code and drive code reviews in GitHub, query and transform data with SQL; partner … closely with data engineering to model lineage and build reliable pipelines using dbt on Snowflake (or similar modern data stack). You will apply traditional ML where appropriate (classification, anomaly detection, NLP, forecasting) and integrate with GenAI approaches; choose the simplest method that meets risk and performance requirements. Additionally ...

discover, experiment, develop and productionise ML and AI models at Compare the Market. You’ll partner closely with product, engineering and machine learning engineering to take the most important use cases from problem framing and research through to robust, measurable value in production. Set technical direction for complex … high‐priority use cases within a domain using a range of paradigms and frameworks (e.g. supervised, unsupervised, reinforcement learning, foundation models); align with Product & Engineering to deliver outcomes to agreed timelines and quality standards. Modelling, Productionisation & Standards Apply and contribute to best practices for experimentation, modelling and measurement (including ...

Science, Artificial Intelligence, or a closely related field (or equivalent experience) Strong foundation in AI/ML concepts and practical experience with data analysis, feature engineering, and model development Experience working with large, complex datasets and applying statistical analysis Hands-on experience training, deploying, and maintaining machine learning ...

FEQ127R163 Location: London Skills: Data Science, Machine Learning, AI, LLM, GenAI As a Senior Specialist Solutions Architect (Srv SSA) - ML Engineering, you will be the trusted technical ML expert to both Databricks customers and the Field Engineering organisation. You will work with Solution Architects to guide customers … training/inference optimisation, integration with cloud-native services and MLOps Provide advanced technical support to Solution Architects during the technical sale, ranging from feature engineering, training, tracking, servin,g to model monitoring, all within a single platform, and participating in the larger ML SME community in Databricks ...

uses machine learning to turn business insights into business success. As a Machine Learning Engineer, you'll sit at the intersection of data science, engineering, and commercial strategy, working closely with our product and core engineering teams to translate business challenges into deployable ML solutions. You'll have … focussed, product led business. In return this ML Engineer will receive extensive growth and personal development opportunities as the business transitions away from legacy engineering practices. This ML Engineer based near Birmingham should have most of the following key skills: - Demonstrated experience delivering business impact and growth through ...

offers the chance to make a significant impact within an innovative, tech-driven organisation. You'll work at the forefront of data modelling, analytics engineering, and AI-enablement, helping shape scalable data products that power enterprise reporting, machine learning, and self-service insights. Senior Analytics Engineer/Data Modeller … data consistency across domains. Collaborate with data engineers to support robust ETL/ELT pipelines and maintain end-to-end data lineage. Deploy analytics engineering solutions using dbt, SQL transformations, and CI/CD best practice. Partner with analysts and data scientists to deliver performant and reliable datasets. Implement ...

acquisition efficiency), providing critical insights to our marketing and commercial teams. Own the complete development lifecycle for your machine learning models, from data gathering, feature engineering, and POC to model training, validation, and production deployment. Partner with our Machine Learning and Software Engineering teams to deploy your ...

most challenging problems in Defence and Security. What We’re Looking For Strong experience (7+ in data science lifecycle: data collection/engineering, cleaning and processing large datasets, feature engineering, and building predictive/statistical models. Solid programming skills, especially in Python (or R), and familiarity with ...

assessment. Collaborate with electronics engineers to interface machine learning models with handheld and wearable sensor systems Develop pipelines for real-time data acquisition and feature extraction and evaluate model performance and system-level integration Establish rigorous data governance and pre-processing protocols to ensure data integrity, security, and compliance … practice through collaborations, providing training and helping to secure research funding About you: PhD or equivalent industrial experience in Computer Science, Data Science, Biomedical Engineering, Applied Mathematics, or a closely related discipline with a focus on machine learning or data-driven modelling Proven expertise in developing, training, and validating ...

data reliability and performance, and enabling teams to derive meaningful insights and value from data. The successful candidate combines deep technical expertise in data engineering and ML workflows with a strategic mindset and a strong understanding of trading-related data models and compliance requirements. Job Description Strategic Leadership Define … evolution with enterprise and application architecture principles. Ensure data systems meet performance, cost, and scalability targets across multiple environments. Drive the adoption of data engineering best practices that balance agility with operational excellence. Governance, Quality & Compliance Enforce and maintain robust data governance across the full lifecycle, including data lineage ...

Productivity capability—designing, training, and deploying models with MLflow/AutoML, and integrating them into real business processes. You’ll collaborate across disciplines (Data Engineering, Security, Product) and work with services such as Azure Storage, Azure DevOps/GitHub Actions, and Fabric/Power BI to ensure solutions … designing, training, registering, and deploying models using Azure Machine Learning (AML), AutoML, and MLflow.Proficient in Python, pandas, and scikit-learn for data science and feature engineering, with a strong focus on rigorous validation and experime nt tracking.Skilled in deploying models to real-time REST endpoints and orchestrating batch ...

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 ...

machine learning role Strong programming skills in Python and familiarity with key data libraries (e.g. pandas, NumPy, scikit-learn) Experience with data wrangling , feature engineering, and model optimisation Understanding of data pipelines , APIs, and production deployment workflows Excellent communication skills and a collaborative approach Why Apply? Work ...

Analyse datasets to identify patterns, trends, and actionable insights. Support the development and evaluation of machine-learning models. Assist with data cleaning, preparation, and feature engineering. Conduct statistical analysis to support business decisions. Build reports, dashboards, and visualisations for internal stakeholders. Collaborate with technical and non-technical teams ...

Analyse datasets to identify patterns, trends, and actionable insights. Support the development and evaluation of machine-learning models. Assist with data cleaning, preparation, and feature engineering. Conduct statistical analysis to support business decisions. Build reports, dashboards, and visualisations for internal stakeholders. Collaborate with technical and non-technical teams ...

solution opportunities. Lead the design, development, prioritisation, and execution of AI initiatives, ensuring they meet business and technical requirements. Oversee data analysis, preprocessing, and feature engineering for robust model development. Champion AI projects from concept to production, including integration, monitoring, and performance evaluation. Manage complex matrix stakeholder relationships ...