19 of 19 Permanent Feature Engineering Jobs in the UK excluding London

Machine Learning, Artificial Intelligence, Predictive Analytics, Statistical Modelling, Python, SQL, PySpark, Azure, Databricks, MLflow, GitHub Actions, CI/CD, Time Series Forecasting, Propensity Modelling, Feature Engineering, Data Engineering, Azure Machine Learning, Azure Data Platform, Experiment Design, A/B Testing, Hypothesis Testing, Predictive Modelling, Customer Analytics, Marketing … that improve customer outcomes, enhance commercial performance & support strategic business decision making. Own the complete analytical lifecycle, from initial problem definition & exploratory analysis through feature engineering, model development, deployment, operational monitoring & continuous optimisation. Build sophisticated statistical & machine learning models covering areas such as: * Customer Lifetime Value * Customer Propensity ...

systems: devices that operate autonomously, make decisions in real time, and remain reliable under the constraints that define actual field deployment. The Challenge The engineering challenge is significant. You will be responsible for the complete lifecycle of machine learning models that run on embedded devices. This means: From Sensor … transform this stream into a robust, real-time classification model that runs on hardware with severe constraints on memory, computation, and power. Engineering Under Constraint. Every machine learning decision you make has downstream consequences for embedded systems. A model that requires 512MB of RAM will ...

natural language processing [NLP]/and neural networks [NN]) you will be part of a small, central function that partners closely with product and engineering teams on a single, shared roadmap, with a one‐team mentality throughout. We take a test‐and‐learn approach: real experiments, time‐boxed … data with external reference sources to support faster, better decisions. Deployment & monitoring. Deploying and monitoring machine learning (ML) models in production, with the engineering discipline to catch drift and issues early. Cross‐team support. Occasional collaboration on NLP/NN‐related work led by our existing senior data scientist ...

science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation …/ML solutions aligned to Army training objectives and enterprise architecture principles. Support the development and maintenance of 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. ...

positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engage them. Within Advertising Engineering, the MarTech team builds the products, services, and machine learning systems that help Roku deliver the right communication, creative, and marketing experience … pair a global mindset with locally relevant execution. You should be a gritty problem solver and self-starter who can work effectively with engineering, product, data science, and commercial stakeholders across Roku. The successful candidate will display a balance of hard and soft skills, including the ability to respond ...

positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engage them. Within Advertising Engineering, the MarTech team builds the products, services, and machine learning systems that help Roku deliver the right communication, creative, and marketing experience … using code for statistical analysis and tool building, using both general‐purpose software and statistical languages. What You’ll Be Doing Data Analysis/Feature Engineering: Apply your expertise to identify and calculate features that can be leveraged by multiple use cases as well as models. Train Machine ...

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 … Generative AI, AI-assisted code generation, automated testing, code review acceleration, agentic workflows, and development process optimisation. This role involves providing technical leadership, engineering expertise, and tooling oversight across the software delivery lifecycle, helping teams apply AI responsibly to modernise platforms, improve code quality, streamline delivery, and enhance developer ...

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 ...

practices across the function Design and deploy machine learning models across forecasting, customer segmentation, and propensity modelling Own end-to-end model development including feature engineering, validation, deployment, and monitoring Partner with Engineering and Product teams to build scalable, production-ready data science solutions Translate analytical outputs ...

offer . Job Description About the role: Join us as a Software Engineer in our critical Scam Prevention team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base. How we work … securing customers' money, accelerating product growth by raising automation levels, and helping us engineer a world-class money transfer product. What do you need? Engineering Expertise: Professional experience with Java or other JVM-based languages, including the Spring framework. Experience building and designing scalable web applications that handle large ...

ensuring high-quality, scalable model delivery across fraud and transaction monitoring use cases. Drive end-to-end model lifecycle ownership — from data exploration and feature engineering to deployment, monitoring, and performance optimisation. Provide hands‐on technical leadership, reviewing Python code, model design, distributed computing approaches, and architectural decisions. ...

research-only environment. You'll work on real business problems, build machine learning models that drive decision-making, and collaborate closely with engineering teams to see your work deployed and used at scale. What you'll be doing: Partnering with stakeholders to turn business challenges into Data Science solutions … looking for: Commercial experience as a Data Scientist Strong Python and SQL skills Hands-on experience building Machine Learning models Expertise in feature engineering, model evaluation and model selection Experience working with large datasets Exposure to Azure, AWS or GCP Strong stakeholder management and communication skills Experience taking ...

Build and maintain scalable data science products, including predictive models, forecasting solutions, segmentation, recommendation engines and experimentation frameworks that support business decision-making. Data Engineering & Model Productionisation: Develop robust analytical datasets and machine learning pipelines using Databricks, Python, SQL and Spark, ensuring solutions are scalable, reliable and production-ready. … learning workflows using Databricks, Spark or similar large‐scale data processing technologies. Machine Learning & Statistical Expertise: Deep understanding of supervised and unsupervised machine learning, feature engineering, model evaluation, experimentation and performance monitoring techniques. Retail & Commercial Analytics: Experience applying data science in retail, consumer, grocery, apparel or other high ...

Europe (Remote), Europe (Remote), United Kingdom Contract Location: Brighton (Hybrid)/Europe (Remote) About Attercop Attercop is a knowledge engineering and agentic AI company built specifically for private equity and professional services. We turn fragmented, hard to use information into structured intelligence and deploy autonomous AI agents that make … transformation. Role Overview You’ll design, build, and integrate advanced AI models into real software systems. This role sits at the intersection of software engineering, data science, and MLOps,turning research into robust, scalable, production-ready AI services. Core Responsibilities Build functional AI services from architectural designs Orchestrate data ...

Data Science team of a large, established financial services business. The company has invested in its data platform and is building a dedicated ML Engineering capability to get more models into production. You'll work on real business problems, using large and varied datasets to develop models that … initial experimentation. You should be comfortable with: Python and common data science libraries. SQL and working with large datasets. Statistical modelling and machine learning. Feature engineering, model selection and evaluation. Writing clear, maintainable and testable code. Git-based development workflows. Working in a cloud environment such as Azure ...

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 ...

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 ...

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 ...