13 of 13 Permanent Feature Engineering Jobs in the UK excluding London

Lead, Applied Scientist and Research Engineer positions—for upcoming roles across applied machine learning, generative AI, MLOps and model productionisation. These are hands-on engineering roles where you'll build, train, ship and operate the models that drive real product behaviour and real business outcomes. You'll work across … lifecycle—from problem framing and data preparation through to model development, evaluation, deployment, monitoring and iteration. The role suits someone who pairs solid software engineering foundations with genuine ML rigour and a healthy scepticism about what models can and can't be trusted to do. Key Responsibilities Partner with ...

Python and SQL skills Experience developing and deploying machine learning models into production environments Excellent understanding of statistical modelling, experimentation, and model evaluation Strong feature engineering and exploratory data analysis capabilities Experience communicating technical findings and insights to non-technical stakeholders A degree qualification (BSc, MSc, PhD etc. … innovation The Senior Data Scientist role will involve: Developing and deploying machine learning models to solve real-world business challenges Performing exploratory data analysis, feature engineering, model development, and evaluation Building forecasting, classification, segmentation, and predictive modelling solutions Designing and executing statistical analyses and experiments to support strategic ...

machine learning. Key Responsibilities Apply statistical and machine learning techniques to solve complex business and operational challenges. Perform data cleaning, transformation, and feature engineering across large and diverse datasets. Build, train, validate, and optimise machine learning models. Translate technical findings into clear insights for both technical … technical stakeholders. Collaborate with engineering teams to deploy models into real-world environments. Keep up to date with developments across AI, machine learning, and data science. What we need from you: Strong Python programming skills with experience across data science and machine learning workflows. Solid understanding of machine learning ...

deployment of AI/ML solutions aligned to Army training objectives and enterprise architecture principles. Develop and maintain ML pipelines including data preprocessing, feature engineering, model training, validation, and performance evaluation. Support integration of AI capabilities into secure operational environments, ensuring compatibility with DevSecOps pipelines and platform constraints. … . Experience building and maintaining end-to-end ML pipelines (data ingestion, pre-processing, training, evaluation, deployment) and deployment to production environments. Understanding of feature engineering, model validation, and performance evaluation techniques. Experience integrating ML components into wider software systems via APIs or microservices. Experience working with version ...

Work With Building and deploying AI and Machine Learning solutions Designing and implementing end-to-end AI and ML pipelines, from data acquisition and feature engineering through to deployment and optimisation Developing scalable ML pipelines and engineering frameworks AI model training, evaluation, optimisation and deployment Cloud-native … stakeholders to understand business challenges and translate requirements into AI solutions Working closely with technical and non-technical teams throughout programme delivery Cross-functional engineering, architecture and data teams Agile software development and delivery methodologies Exploring and adopting emerging AI technologies and approaches to drive innovation and business value ...

concept into production environments Develop scalable ML pipelines using AWS cloud technologies Implement MLOps and LLMOps best practices for deployment, monitoring and governance Support feature engineering, model optimisation and performance monitoring Apply responsible AI principles, including model explainability and fairness Present findings and recommendations to technical … tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge of Generative AI, LLMs, prompt engineering and RAG architectures Experience with LLMOps tools such as LangChain, LangSmith or LangGraph Strong understanding of model monitoring, validation and governance Excellent communication ...

play a key role in designing, developing and deploying AI and Machine Learning solutions, working across the full ML lifecycle from data preparation and feature engineering through to model deployment and optimisation. Working with Python, SQL and leading ML frameworks, you'll build scalable pipelines, develop and evaluate ...

here at Sky. Role/Team overview We are seeking an AI Specialist to design, build, and operationalise intelligent systems that enhance Site Reliability Engineering (SRE) platforms and automate large-scale infrastructure operations. This role has a strong emphasis on reliability, scalability, and operational efficiency. You will work closely … with SRE, platform, and cloud engineering teams , within a global technology support organisation to embed AI-driven decision-making, predictive analytics, and autonomous remediation into infrastructure platforms . What youll do Infrastructure Automation at Scal e Design and deploy AI-powered automation frameworks for incident response and remediation (self ...

using Python, TensorFlow, PyTorch Work on supervised, unsupervised, and reinforcement learning problems Clean and process large datasets to extract insights and train algorithms Perform feature engineering to improve model accuracy Design ML pipelines and automate model deployment Collaborate with software engineers to integrate models into applications Use MLOps ...

complex real-world environment. You'll be involved in: Developing machine learning models to improve forecasting and operational planning Applying time-series analysis and feature engineering techniques across large datasets Building and improving discrete event simulation models to test different scenarios Identifying trends, patterns and potential operational constraints … Python experience beneficial) SQL and working with large datasets Ability to explain technical findings clearly to different audiences A background within transport, logistics, aviation, engineering, manufacturing, supply chain or similar operational environments would be highly advantageous. This would suit a Data Scientist who enjoys modelling how things work, testing ...

typically lead a team or the solution delivery effort, demonstrating technical excellence through leading by example. You could be providing technical support, leading an engineering team or working across multiple teams as a subject matter expert who is critical to the success of a large programme of work. Your … deployments. Shape team behaviour for writing specifications and acceptance criteria, estimating stories, sprint planning and documentation. Actively define and evolve PA’s data engineering standards and practices, ensuring we maintain a shared, modern and robust approach. Lead and influence technical discussions with client stakeholders to achieve the collective ...

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 ...

data to trading infrastructure, where speed and reliability are fundamental requirements Building integrated environments where quantitative researchers develop, test, and deploy predictive models - from feature engineering through execution Architecting cloud-based simulation and experimentation platforms that support large-scale quantitative research without becoming a bottleneck Standing up toolchains … need to understand how data, models, and trading systems interact. You can work productively with quants and understand what they need from the engineering side. You are senior enough to take ownership. CTO wants people he can hand large initiatives to and trust the output. 6 to 15+ years ...