19 of 19 Permanent Feature Engineering Jobs in England

recommendations. Build AI-powered HR solutions, including NLP, generative AI, and LLM applications. Conduct ONA, workforce segmentation, and employee sentiment analysis. Partner with HRIS, engineering, and business teams to design scalable data pipelines and deploy ML/AI models. Create dashboards and visualisations that bring workforce insights to life … ability to translate complex technical analyses into clear, actionable insights for non-technical audiences. Familiarity with vector databases, embedding-based retrieval, and prompt engineering to support AI-enabled HR solutions. Understanding of ethical AI principles, bias detection, and responsible AI practices in HR contexts. Technical/Professional Qualifications Degree ...

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 ...

machine learning. Key Responsibilities: Contribute to the development of predictive and statistical models addressing business-critical challenges across diverse domains. Conduct exploratory data analysis, feature engineering, and hypothesis testing to uncover patterns and support model development. Collaborate with senior data scientists and ML engineers to refine models, improve ...

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 ...

/ML, including leading teams and projects from conception to production 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 ...

/ML, including leading teams and projects from conception to production 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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

support commercial growth and enhance customer experiences and outcomes. Leading and supporting end-to-end data science projects, including business case development, solution design, feature engineering, model development, deployment, and MLOps. Taking ownership of existing ML/AI projects, including ongoing monitoring of model performance, data drift, scoring ...

application of advanced analytics and machine learning techniques that answer complex business questions and drive strategic decisions. You'll work closely with data engineering and business teams to design models and analytical solutions that improve customer experience, optimise operations, and support financial and strategic planning.This role combines technical expertise … clearly to technical and non-technical audiences, and ensure best practices in analytical workflows. Technical Delivery: Engineer and optimise analytical and spatial SQL, build feature enrichment pipelines, develop and evaluate ML models, and package outputs for deployment. What You'll Need to Succeed Strong experience in applied machine learning ...

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 ...