1 to 25 of 26 Feature Engineering Jobs in London

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 ...

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 ...

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 ...

machine learning and deep learning models. Work on AI/ML projects including NLP, computer vision, recommendation systems, and generative AI. Perform data cleaning, feature engineering, and exploratory data analysis (EDA). Build and manage data pipelines and model training workflows. Deploy models into production and monitor performance. … Collaborate with Product, Engineering, and Business teams to translate business problems into AI solutions. Conduct model evaluation, A/B testing, and performance tuning. Document models, experiments, and technical processes. Required Skills & Qualifications Classic Machine learning (Regression, predictive Analysis, Classification, Clustering) Machine learning Model Optimisation Strong proficiency in Python ...

work on Build and improve ML/AI models that solve measurable business problems Take ownership of end-to-end workflows: data ingestion → feature engineering → modelling → evaluation → deployment Run experiments, quantify impact, and iterate fast (including A/B testing where appropriate) Partner with engineering and product … modern ML tooling What we’re looking for A recently completed Master’s degree (Russell Group preferred) in Data Science, Computer Science, Mathematics, Physics, Engineering, or similar Excellent Python skills and ML foundations (e.g. pandas, NumPy, scikit-learn; strong coding practices matter) Strong grasp of model evaluation, statistics ...

critical role in designing, building, and maintaining data pipelines and infrastructure that enable the development and deployment of machine learning models and drive engineering excellence. You will collaborate closely with data scientists, and lead ML engineers, and software engineers to ensure data is clean, accessible, and optimised for large … systems (e.g., PySpark, Hadoop). Data Preparation: Collaborate with data scientists to prepare and transform raw data into formats suitable for machine learning, including feature engineering and data augmentation. Automation: Implement automation tools and frameworks (CI/CD) to streamline the deployment and monitoring of machine learning models ...

clients. As a senior leader, you will interact frequently with customers, provide expert opinions, and contribute to HCL’s strategic vision. Key Responsibilities Technical & Engineering Leadership • Design and implement AI and cloud architectures, integrating GenAI technologies to enhance functionality and scalability. • Lead architectural discussions with clients, providing expert guidance … Skills & Experience • Deep knowledge of machine learning operations (MLOps) and experience in deploying, monitoring, and maintaining AI models in production environments. • Proficiency in data engineering for AI, including data preprocessing, feature engineering, and pipeline creation. • Expertise in AI model fine-tuning and evaluation, with a focus ...

Assist in developing and evaluating predictive and analytical models using statistical and machine learning techniques 🛠 Support data pipelines, including data collection, cleaning, and feature engineering 📊 Create dashboards, visualisations, and reports that translate data into clear, actionable insights 🤝 Work closely with analysts, engineers, and stakeholders to support data-driven ...

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 ...

other AI applications. Experiment with algorithms and optimize hyperparameters for performance. Data Preparation Collect, clean, and preprocess large datasets for training and validation. Implement feature engineering and data augmentation techniques. Integration & Deployment Develop APIs or services to integrate ML models into production systems. Work with MLOps tools … practices. Implement bias detection and mitigation strategies. Your Profile Essential Skills/Knowledge/Experience (Up to 10) 10+ years of experience in software engineering, with 5+ years in AI/ML. Expert in Python, PyTorch, TensorFlow, and NLP frameworks. Proven experience with LLMs, transformer architectures, and LangChain/ ...

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 ...

Collaborate with data engineers, analysts, and product teams to translate business needs into AI-driven solutions Contribute to the development of data pipelines and feature engineering workflows Integrate models into production using APIs, batch jobs, or real-time systems Apply best practices around experimentation, evaluation, versioning, and monitoring ...

models for user personalisation, including recommendation systems, ranking models, user segmentation, and content understanding, with a strong focus on TensorFlow-based development. Data Pipeline Engineering: Build and maintain scalable data pipelines to support feature engineering and model training across large structured and unstructured datasets, leveraging cloud‐native … relevance. Experimentation: Lead A/B testing and offline experimentation to evaluate model performance and guide ongoing improvement. Cross‐Functional Collaboration: Work closely with engineering, product, data, and research teams to ensure ML solutions align with product and business goals. Research & Innovation: Stay informed on advances in machine learning ...

Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings. This is a hands-on role … impact. Key Responsibilities Translating complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. ...

Outside IR35 Clearance: Active SC Clearance required Email : henry.clay-davies@searchability.com Phone : 07719 065951 Overview We are seeking an experienced Data Science/Data Engineering Contractor to join a high-impact programme based in London, working on advanced data-driven and LLM-enabled platforms. This is an outside IR35 … data solutions Ensure data solutions meet security, performance, and maintainability standards expected in secure environments Required Skills & Experience Strong commercial experience in data engineering and/or data science roles Hands-on experience building data pipelines and AI-enabled workflows using LangChain and/or LangGraph Excellent Python development ...

Develop and support analytical and statistical models using Python 🛠 Work with real-world energy and environmental datasets, including data cleaning, validation, and feature engineering ☁️ Use AWS services to support data storage, processing, and analytics workflows 🗄 Query and manipulate structured datasets using SQL 📊 Build reports, dashboards, and visualisations that … tailored to experience, including bonus, pension, and generous annual leave ✅ What we’re looking for: 🎓 A degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field 💼 0–2 years of experience in data analysis or data science (graduate roles, internships, placements, or academic projects welcome) 🐍 Strong ...

things that go into production, and wants to learn from experienced engineers in a fast-moving environment. You’ll be part of a modern engineering function working on large-scale data and AI products, contributing to model development, data pipelines, and deployment workflows that power mission-critical platforms. … Build, train, and evaluate machine learning models using Python 📊 Work with large, complex datasets to support AI-driven products and insights 🧠 Assist with feature engineering, model experimentation, and performance optimisation ☁️ Contribute to data and ML pipelines in cloud-based environments 🗄 Work with structured and semi-structured data using ...

advanced graph analytics models and algorithms to uncover patterns, anomalies and relationships within large-scale graph datasets. Collaborate with cross-functional teams including product, engineering, and business stakeholders to understand data requirements and deliver impactful solutions. Implement and optimise graph databases and graph processing frameworks (e.g., Neo4j). Develop … predictive models using machine learning techniques tailored for graph-structured data (e.g., node classification, link prediction, community detection). Perform data pre-processing, feature engineering, and exploratory data analysis on structured and unstructured datasets. Communicate complex data insights clearly and effectively to technical and non-technical audiences. Mentor ...

optimisation project. You will design and implement predictive and prescriptive models for Maintenance, Repair, Overhaul AI Solutions. Performing exploratory data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modelling. Communicate findings and recommendations to business stakeholders. Continuously improve models based on feedback and operational ...

redaction middleware, retrieval allow-lists, and per-use-case policies. Add evaluation gates for answer quality and safety in pipelines, implement canary deployments with feature flags, and automate rollbacks on drift. Manage the lifecycle of models, including fine-tuning with consented datasets, synthetic augmentation policies, and maintaining model registry … GenAI solutions in production. Additional Skills & Qualifications A broader understanding of machine learning algorithms. Exposure to multimodal AI (text + vision, speech). Data engineering and analysis skills including ETL pipelines and feature engineering. Familiarity with MLOps/DevOps pipelines, monitoring, and retraining. Understanding of knowledge graphs, embeddings ...

ability to translate insights into business impact.Key Responsibilities Design and implement predictive and prescriptive models for MRO AI Solutions. Perform exploratory data analysis and feature engineering. Collaborate with Data Engineers to ensure data readiness for modelling. Communicate findings and recommendations to business stakeholders. Continuously improve models based on feedback ...

Supporting Credit Card growth, including new acquisition scorecards as volume increases through upcoming Experian integration Owning the entire modelling process - from data extraction and feature engineering through to deployment (no separate engineering hand-off) REQUIREMENTS Strong data science/modelling experience using ML techniques Background in Financial ...

value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Act as a technical lead … with cross-functional teams, including engineers, product leads, and client stakeholders Bachelor’s or Master’s degree in a quantitative field (e.g., Mathematics, Physics, Engineering, Computer Science) from a strong university Excellent communication skills and a collaborative mindset Please note: This role cannot offer VISA sponsorship ...

large language models, agentic AI – across research, rankings, submissions and product innovation. Oversee the end-to-end analytics lifecycle, from data acquisition and feature engineering through to model development, validation, deployment and monitoring Ensure AI-driven outputs are explainable, transparent and aligned with Chambers’ standards and reputation ...

model lifecycle. This isn't a traditional "build and hand off" role, you'll manage everything from data collection to feature engineering, model development, testing, and deployment. Key Responsibilities: Develop credit risk predictive models, including scorecards, income models, and early repayment models. Build automation for lending decisions … Create forecasting and marketing models to support customer segmentation and growth strategies. Own the full modelling process, from raw data through deployment, without separate engineering teams. Collaborate with cross-functional teams to ensure models are robust, actionable, and scalable. Continuously improve modelling approaches as volumes and portfolios expand. REQUIREMENTS ...