18 of 18 Permanent Feature Engineering Jobs in the UK excluding London

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 ...

across health and safety, sustainability and ethical behaviour. As a Data Scientist, you'll join a growing, highly skilled team spanning data science, data engineering, AI engineering and DevOps. You'll play a key role in building and deploying machine learning and AI solutions that power business applications … Models, with the chance to integrate innovative AI capabilities including LLMs, MCPs, APIs and enterprise data into production platforms. You'll work closely with Engineering and Product teams in a collaborative Agile environment, turning complex data and technology into solutions that deliver tangible business value. The role will include ...

across health and safety, sustainability and ethical behaviour. As a Data Scientist, you'll join a growing, highly skilled team spanning data science, data engineering, AI engineering and DevOps. You'll play a key role in building and deploying machine learning and AI solutions that power business applications … Models, with the chance to integrate innovative AI capabilities including LLMs, MCPs, APIs and enterprise data into production platforms. You'll work closely with Engineering and Product teams in a collaborative Agile environment, turning complex data and technology into solutions that deliver tangible business value. The role will include ...

have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III at JPMorganChase within the Corporate Technology, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products … uses these insights to drive improvements to coding hygiene and system architecture Required qualifications, capabilities, and skills Formal training or certification in software engineering concepts, plus 5+ years of applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem ...

logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling ...

robust, ethical and useful. The role combines technical delivery, stakeholder collaboration and product-minded thinking.You will work with multidisciplinary teams across data, AI, software engineering, product, QA and delivery to create practical outcomes for clients and end users. Key responsibilities Lead the design, development, validation and deployment support … science models and analytical products. Apply advanced techniques such as machine learning, NLP, forecasting, optimisation or simulation where appropriate. Guide colleagues on data preparation, feature engineering, model selection, validation and interpretation. Work with data engineers and software teams to make data science outputs scalable, maintainable and usable. Communicate ...

Lead the development, implementation, and end-to-end delivery of advanced machine learning models and algorithms to drive market operations initiatives. Partner with AI Engineering teams to ensure robust architecture design and deployment patterns for AI/ML models that align with business needs. Mentor and guide a team … managing the machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Experience working with large, complex datasets and applying statistical analysis. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization ...

ensuring high-quality, scalable model delivery across fraud and transaction monitoring use cases. Driveend-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. Manage ...

analytics, AI/ML capabilities and operational intelligence systems. This is an opportunity to work on technically challenging projects where you’ll influence architecture, engineering approaches and the delivery of high-impact data capabilities. What You’ll Be Doing Designing and developing modern data platforms and pipelines Building scalable … across data services Working closely with clients and multidisciplinary teams to solve complex data challenges What We’re Looking For Commercial experience delivering Data Engineering solutions Strong Python and SQL skills, with experience of Java or Scala beneficial Experience building large-scale ETL/ELT and data processing pipelines ...

analytics, AI/ML capabilities and operational intelligence systems. This is an opportunity to work on technically challenging projects where you’ll influence architecture, engineering approaches and the delivery of high-impact data capabilities. What You’ll Be Doing Designing and developing modern data platforms and pipelines Building scalable … across data services Working closely with clients and multidisciplinary teams to solve complex data challenges What We’re Looking For Commercial experience delivering Data Engineering solutions Strong Python and SQL skills, with experience of Java or Scala beneficial Experience building large-scale ETL/ELT and data processing pipelines ...

Schedule Full time Job Shift Day Job Description We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III – DevOps/AWS Engineer at JPMorganChase within the Commercial & Investment Bank, particularly in the Payments Technology … quality production code; review and debug code written by others to ensure reliability, performance, and maintainability. Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, accelerated test strategy, incident/root-cause ...

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 ...

models (not just consuming APIs) • A solid understanding of model evaluation and validation, overfitting and bias/variance trade-offs, and data quality and feature engineering • Proficiency in Python and ML frameworks such as PyTorch or TensorFlow • Experience building and maintaining ML pipelines in production • Familiarity with ...

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 ...

taking MLmodels from prototype through to production Strong experience with Google Cloud Platform, BigQuery and Vertex AI Strong Python and SQL skills Experience in feature engineering, statistical validation and modelevaluation Comfortable working with messy, imperfect real-world data rather than cleanbenchmark datasets Able to explain model outputs clearly ...

doing Develop and deploy ML and statistical models across credit risk, affordability and pricing Own models end-to-end, including data, feature engineering, modelling, validation, deployment and monitoring Build model monitoring frameworks and performance dashboards Explore new data sources, challenger models and A/B testing to improve ...

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 ...