1 to 25 of 56 Permanent Feature Engineering Jobs in the UK excluding London

looking for a Senior Data Engineer with a machine learning focus to join our data team, taking ownership of the data and feature pipelines that production ML systems depend on, training data preparation, feature engineering, and the path from a model that works in a notebook … ambiguous problems across client engagements, partnering closely with data scientists and ML engineers, while mentoring junior engineers and helping to raise the bar on engineering practice. The foundations still matter: this is a data engineering role at heart, built on Python, PySpark, and platforms like Databricks, Snowflake ...

looking for a Senior Data Engineer with a machine learning focus to join our data team, taking ownership of the data and feature pipelines that production ML systems depend on, training data preparation, feature engineering, and the path from a model that works in a notebook … ambiguous problems across client engagements, partnering closely with data scientists and ML engineers, while mentoring junior engineers and helping to raise the bar on engineering practice. The foundations still matter: this is a data engineering role at heart, built on Python, PySpark, and platforms like Databricks, Snowflake ...

looking for a Senior Data Engineer with a machine learning focus to join our data team, taking ownership of the data and feature pipelines that production ML systems depend on, training data preparation, feature engineering, and the path from a model that works in a notebook … ambiguous problems across client engagements, partnering closely with data scientists and ML engineers, while mentoring junior engineers and helping to raise the bar on engineering practice. The foundations still matter: this is a data engineering role at heart, built on Python, PySpark, and platforms like Databricks, Snowflake ...

About The Role Why choose us? BRUSH Group provides the energy solutions that help power our built world. From power transformers to switchgear and engineering solutions, for generations, the BRUSH brand has stood for engineering excellence. We are committed to supporting the global effort for industrial decarbonisation … analytical expertise with strong commercial curiosity. The Data Scientist will own selected use cases across the full lifecycle—from problem definition, data exploration and feature engineering through to model development, deployment, monitoring and continuous improvement and will be accountable for demonstrating measurable operational or commercial value. The role ...

deliver measurable commercial value. You'll be working on business critical projects from day one, identifying opportunities and shaping hypotheses through to data exploration, feature engineering, model development, and deployment. Working with large and complex datasets, you'll use Python, PySpark, SQL, and Azure Databricks to develop robust … measurable commercial outcomes Explore, profile, and analyse large and complex datasets to identify trends, opportunities, and features that improve model performance Apply statistical techniques, feature engineering, and model tuning to create robust and scalable analytical solutions Collaborate with Data Engineers and ML Engineers to operationalise models and embed ...

delivering successful, production‐scale machine learning solutions (ideally on AWS SageMaker). You will provide technical leadership across ML lifecycle, including defining architecture, engineering standards, MLOps practices, and governance frameworks for a large‐scale matching platform. This is a hands‐on lead role requiring recent expertise in building, deploying … success designing and delivering enterprise‐scale ML platforms and products (ideally using AWS SageMaker). Proven experience delivering ML solutions from data ingestion and feature engineering through to production deployment, monitoring, and continuous improvement. Experience building reliable, low‐latency inference services and operating ML workloads at scale. Proven ...

full data science journey, from exploring and experimenting with rich datasets to deploying robust, scalable solutions into production. Working closely with colleagues across engineering, product and operations, you’ll translate real business questions into practical, impactful insights—bringing curiosity, collaboration and clarity to everything you do. What … development and deployment of machine learning models and analytical solutions , from data exploration through to production. Making day-to-day technical decisions on feature engineering, model selection, analytical techniques and data requirements within agreed team standards. Resolving technical challenges during model development and deployment, seeking guidance from ...

full data science journey, from exploring and experimenting with rich datasets to deploying robust, scalable solutions into production. Working closely with colleagues across engineering, product and operations, you’ll translate real business questions into practical, impactful insights—bringing curiosity, collaboration and clarity to everything you do.**What … development and deployment of machine learning models and analytical solutions**, from data exploration through to production.- **Making day-to-day technical decisions** on feature engineering, model selection, analytical techniques and data requirements within agreed team standards.- **Resolving technical challenges** during model development and deployment, seeking guidance from ...

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 Familiarity with LLMOps tooling such as LangSmith, LangChain, or LangGraph Understanding of model evaluation, validation techniques, and production monitoring Experience working ...

Senior AI Engineer (Autonomy & Machine Learning) ALTEN is a global engineering and technology consultancy operating across over 35 countries worldwide. We partner with industry leaders across sectors including Aeronautics, Aerospace, Defence, Naval, Automotive, Energy, Rail, IT and many more to deliver innovative engineering solutions that drive technological advancement … edge artificial intelligence and machine learning capabilities that support high‐impact programmes across the defence and aerospace sectors. Working as part of a multidisciplinary engineering team, you’ll design, build and deploy robust AI solutions, helping customers unlock the value of their data while driving innovation across advanced autonomy ...

Senior AI Engineer (Autonomy & Machine Learning) ALTEN is a global engineering and technology consultancy operating across over 35 countries worldwide. We partner with industry leaders across sectors including Aeronautics, Aerospace, Defence, Naval, Automotive, Energy, Rail, IT and many more to deliver innovative engineering solutions that drive technological advancement … edge artificial intelligence and machine learning capabilities that support high‐impact programmes across the defence and aerospace sectors. Working as part of a multidisciplinary engineering team, you’ll design, build and deploy robust AI solutions, helping customers unlock the value of their data while driving innovation across advanced autonomy ...

Description Purpose of the role To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. Accountabilities Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code … Senior AI Software Engineer, you will play a key role in designing, developing, and implementing intelligent software solutions that drive innovation, improve engineering productivity, and deliver measurable business value. You will work closely with AI Architects, Data Engineers, Data Scientists, Product teams, and Engineering colleagues to build scalable ...

into one unit that will drive cutting-edge development in a number of critical areas for the business. The role sits within the Data Engineering team and reports to the Head of Data Engineering. The team’s remit is to drive innovation & revenue through the development & delivery of revenue … generating/client-facing data engineering solutions used across the agency. The Senior Data and ML Engineer will be part of a growing team that delivers highly impactful data solutions across our extensive client portfolio and also the agency’s own product offerings. We seek individuals who are proactive ...

classification, LLM, recommendation systems, etc.), Selecting and optimizing algorithms (regression, tree-based models, neural networks, etc.), Integrating models into production environments, Performing data cleaning, feature engineering, and model validation, Identifying tools and specifying processes Mentoring junior team members and contributing to solution architecture, Preparing and presenting analytical results ...

approaches to Thales UK's internal catalogue of capabilities, accelerating responsible AI adoption across programmes. The role will connect with data, digital, research and engineering specialists across Thales UK and Group, maturing emerging AI technologies for future deployment and acting as a technical expert on advanced AI research used … groups to ensure research outputs are trustworthy, human-centred, explainable and suitable for future operational use. Build reproducible research pipelines, including data preprocessing, feature engineering, model training, experiment tracking, evaluation and technical reporting. Ensure Responsible AI practices are embedded throughout the research lifecycle, including robustness, safety, explainability, transparency ...

solutions, not point solutions. Process modelers remain the process experts and co‐own the models. You bring the AI modeling and engineering that makes building, deploying and using models 10x more efficient. You bring deep, hands‐on AI/engineering expertise and the judgement to turn ambiguous technical … first production versions directly for use cases where the path is clear — before the Sr. Solutions Engineer takes them forward to scale. AI‐Native Engineering Operate AI agent workflows (planning, coding, testing, review, documentation) for autonomous prototype delivery — selecting the right level of automation for each engagement. ...

models (predictive, classification, recommendation, LLM-based), Selecting and optimizing algorithms (regression, tree-based, neural networks, etc.), Integrating models into production environments, Performing data cleaning, feature engineering, and model validation, Collaborating with clients and internal teams to translate analytical results into actionable insights, Qualifications We don’t expect ...

analytics team & Tech partners in research to define the knowledge system, the agentic layer across the enterprise. You bring deep, hands‐on AI/engineering expertise and the judgement to turn ambiguous technical problems into shipped, production‐grade systems, while mentoring the engineers around you. Key Responsibilities PoC/… first production versions directly for use cases where the path is clear — before the Sr. Solutions Engineer takes them forward to scale. AI‐Native Engineering Operate AI agent workflows (planning, coding, testing, review, documentation) for autonomous prototype delivery — selecting the right level of automation for each engagement. ...

business teams. Good communication skills with an ability to demystify ML algorithms and capabilities is a must, as stakeholders in ML products include software engineering teams as well as non‐technical business partners. Major Job Responsibilities and Related Duties: Collection, cleaning, and pre‐processing of data for solving business … findings. Collaborate with stakeholders to define requirements and deliverables. Ownership of documentation related to datasets, model selection, training experiments, and inference workflows. Collaborate with engineering teams to integrate ML models into production systems. Monitor ML models in production, setting metrics to identify drift, and establish corrective measures for restoring ...

with minimal oversight. It's not solo delivery: you'll be working closely with a dynamic team spanning ML, MLOps and software engineering, and should be happy to contribute at every level, from early-stage research through to production support. Role & Core Responsibilities Own the delivery of medium-sized … issues and model degradation as a priority. Research new ML applications and improve pre-existing models, sharing findings with the wider ML, MLOps and engineering team. Collaborate closely with product, MLOps and engineering teams to define and prepare new ML applications, contributing meaningfully to planning and grooming. Proactively ...

Your Impact Customer Onboarding & Engine Customization: Lead the technical deployment of our engines for new clients. Partner closely with customers, Customer Success, Product, and Engineering to adapt and customize ML models, ensuring they accurately reflect client‐specific business logic, operational guardrails, and unique data nuances. Analytic Engine Development: Design … implement robust Machine Learning (LightGBM, XGBoost) and Deep Learning (PyTorch) models specifically focused on complex demand sensing and resolving cold‐start forecasting problems. Feature Engineering Pipelines: Build and optimize scalable data pipelines leveraging a hybrid SQL/Python architecture (dbt, Snowflake) to extract rich, localized temporal signals from ...

Build and deploy machine learning models across forecasting, customer segmentation, and propensity modelling Own projects across the full model lifecycle, from data exploration and feature engineering through to deployment and monitoring Partner with Product, Engineering, and commercial teams to deliver scalable analytical solutions Translate complex findings into … with AI-assisted development tools such as GitHub Copilot, Claude, Codex, or similar to improve productivity and code quality Understanding of LLM applications, prompt engineering, and practical AI use cases within analytics workflows Excellent stakeholder management skills with the ability to translate technical outputs into clear business recommendations ...

findings. Collaborate with stakeholders to define requirements and deliverables. Ownership of documentation related to datasets, model selection, training experiments, and inference workflows. Collaborate with engineering teams to integrate ML models into production systems. Monitor ML models in production, setting metrics to identify drift, and establish corrective measures for restoring … Strong mathematical, analytical, and problem-solving skills. Understanding of dataset preparation, splits, data quality control, and management. Knowledge of data pre-processing and feature engineering techniques. Sound understanding of software development best practices and DevOps. Experience with version control systems like Git. Experience with cloud computing platforms like ...

making embedded inside the teams instead of wasting time in wider forums, to reduce time to impact. You bring deep, hands-on AI/engineering expertise and the judgement to turn ambiguous technical problems into shipped, production-grade systems, while mentoring the engineers around you. Key Responsibilities PoC/… first production versions directly for use cases where the path is clear — before the Sr. Solutions Engineer takes them forward to scale. AI-Native Engineering Operate AI agent workflows (planning, coding, testing, review, documentation) for autonomous prototype delivery — selecting the right level of automation for each engagement. ...

will work hand in hand with the automation business and tech teams across R&D and manufacturing. You bring deep, hands‐on AI/engineering expertise in Physical AI and the judgement to turn ambiguous technical problems into shipped, production‐grade systems, while mentoring the engineers around you. … first production versions directly for use cases where the path is clear — before the Sr. Solutions Engineer takes them forward to scale. AI‐Native Engineering: Operate AI agent workflows (planning, coding, testing, review, documentation) for autonomous prototype delivery — selecting the right level of automation for each engagement. ...