1 to 25 of 146 Permanent Feature Engineering Jobs in England

deliver production-grade ML systems for a leading digital gaming and gambling platform. This is a hands-on role combining data science expertise with engineering skills - you'll build models, optimise algorithms, and deploy solutions at scale to enhance customer engagement and decisioning. You'll work closely with Data … science & modelling: Develop, validate, and optimise predictive models using advanced ML algorithms (e.g., gradient boosting, logistic regression, ensemble methods). End-to-end ML engineering: Deploy models as APIs, batch jobs, and streaming services; implement CI/CD, monitoring, and rollback strategies. Feature engineering & pipelines: Build scalable ...

Data & Defence Engineering and Data Science Roles Engineer to Managing Consultant, Defence, & Critical Infrastructure Nationwide Clearance, SC required, DV preferred, some roles sole UK nationals We’re supporting a leading UK technology and transformation consultancy delivering secure AI, data engineering, and advanced analytics across Defence, and critical government …/CD, monitoring, auditability, and governance Contribute to design reviews, estimates, documentation, and bid inputs What you’ll bring Strong experience in data engineering, analytics engineering, or applied data science Cloud and data platform exposure, AWS, Azure, GCP, and/or Databricks Python, ideally PySpark, R helpful ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring. Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails. Design feature engineering approaches and contribute to feature store development. Support production models through monitoring, performance analysis, and continuous improvement. Apply responsible AI practices … governance and quality controls. Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC). Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures. Familiarity with LLMOps tooling (LangSmith, LangChain, LangGraph). Understanding of model evaluation, validation, and production monitoring. Strong problem-solving skills ...

Engineer to design, build and operationalise advanced machine learning solutions that directly support UK national security objectives. This role sits within a multidisciplinary AI engineering environment, working closely with Data Scientists, Software Engineers, Product teams and government stakeholders. The Senior ML Engineer will own the journey from experimentation … including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standards Transitioning validated experiments into production-ready ML services, collaborating closely with engineering teams on deployment and monitoring Building scalable ML pipelines using AWS services and modern experiment tracking frameworks Developing and integrating LLM-powered capabilities ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help You With Them Experience ...

integrate LLM-powered solutions for tracing, evaluation, and production monitoring Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails Design feature engineering approaches and contribute to feature store development Support production models through monitoring, performance analysis, and continuous improvement Apply responsible AI practices … Them Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes ...

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 ...

Partner closely with data scientists to turn experimental models into well-engineered, production-ready systems Develop and maintain end-to-end ML pipelines, including feature engineering, training, evaluation, versioning, monitoring, and automated retraining Contribute to MLOps capabilities, including CI/CD pipelines, model registries, infrastructure automation, and containerised … regulatory requirements Advise business and product teams on opportunities for automation, predictive modelling, and GenAI enablement Contribute to reusable ML components, internal frameworks, and engineering best practices Stay up to date with emerging AI trends, tooling, and foundation models to inform strategic decision-making About You You will ...

this role, you will take ownership of complex models and pipelines, influence technical direction, and mentor less experienced team members while working closely with engineering and product teams. What You’ll Do Design, build, and deploy scalable ML and AI solutions for production environments. Lead model development, evaluation … frameworks such as TensorFlow, PyTorch, or scikit-learn. Experience working with LLMs, NLP, computer vision, or recommendation systems. Solid understanding of data pipelines, feature engineering, and model evaluation. Experience with cloud platforms (AWS, Azure, or GCP) and ML deployment strategies. Strong communication skills and experience mentoring or leading ...

annum Job Type: Full-time, Permanent About The Role We are looking for a talented and motivated Graduate AI Engineer to join our growing engineering team in Cambridge. This is an excellent opportunity for a recent graduate to work on real-world AI and machine learning problems, contributing … driven solutions while developing your technical and professional skills. Key Responsibilities Design, develop, and implement machine learning and AI models Assist in data preparation, feature engineering, and model evaluation Write clean, maintainable, and well-documented code Deploy and monitor models in production environments Collaborate with cross-functional teams ...

Learning models (e.g., classification, regression, clustering, deep learning) to solve complex business problems. Data Wrangling & Analysis: Perform comprehensive Exploratory Data Analysis (EDA), data cleaning, feature engineering, and transformation on large, complex, and sometimes unstructured datasets. Coding & Automation: Write production-quality, highly efficient, and scalable code primarily in Python ...

Learning models (e.g., classification, regression, clustering, deep learning) to solve complex business problems. Data Wrangling & Analysis: Perform comprehensive Exploratory Data Analysis ( EDA ), data cleaning, feature engineering, and transformation on large, complex, and sometimes unstructured datasets. Coding & Automation: Write production-quality, highly efficient, and scalable code primarily in Python ...

algorithms to address business needs, ensuring high accuracy and scalability. Building data pipelines. Design and manage data pipelines that handle large datasets, data preprocessing, feature engineering, and efficient data flow to ensure high-quality input for machine learning models. Optimizing models. Use tools like scikit-learn and Keras ...

frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. •Design and implement ML pipelines on Azure Machine Learning. •Own end-to-end model lifecycle: data ingestion, feature engineering ...

frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. •Design and implement ML pipelines on Azure Machine Learning. •Own end-to-end model lifecycle: data ingestion, feature engineering ...

services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps and GenAI tools (LangChain, LangSmith) Understanding of feature engineering and vector databases Strong grasp of CI/CD practices for ML deployment Why Join Us: Work with niche datasets and cutting-edge tech ...

ability to gut them and work with them past just surface-level functionality. Experience with the full model development lifecycle, from data preprocessing and feature engineering to model validation. Degree in Computer Science, Machine Learning, Computational Chemistry, or equivalent industry experience. Nice To Haves Prior experience in computational ...

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 ...

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 ...