1 to 25 of 28 Permanent Feature Engineering Jobs in the UK excluding London

application asap. Our Solutions & AI Labs (SAIL) practice is looking for an experienced Senior Manager to lead consultancy engagements and grow our AI & Solutions Engineering capability. The Forward Deployed AI & Solutions Engineer role will lead the delivery of AI-enabled solutions embedded in our clients' teams, combining deep technical … solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/ML, Cloud, Platform Engineering, and Managed Solutions. What you will be doing As a Senior Manager in SAIL, you will own and lead consultancy engagements ...

where the NHSBSA can take you. We are people connected to care. Job description Job responsibilities In this role, you are accountable for: AI Engineering and development 1. Designing, developing, and deploying AI solutions from prototype to production, ensuring scalability, security, and maintainability.2. Collaborate on feature engineering … model development, and MLOps. Shares expertise and mentors colleagues and engineers. Excellent understanding of model lifecycle, from experimentation to production. Strong grasp of software engineering principles (SOLID, design patterns), dependency injection, and scalable system design. Strong understanding of NLP, embeddings, and semantic search. Awareness of ethical and privacy implications ...

Data Scientist | Cardiff/Hybrid | Engineering | AI & Predictive Analytics We're supporting a growing engineering business looking to hire a Data Scientist to help develop scalable ML and AI solutions across compliance, risk and contractor analytics platforms. You'll work closely with AI Engineers, Data Engineers and DevOps … learning initiatives that directly support operational performance, compliance and risk management. You'll be involved in the full model lifecycle from data ingestion and feature engineering through to deployment, optimisation and monitoring. Key Responsibilities Develop machine learning models for risk scoring, churn prediction and contractor analytics Build ...

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 ...

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. xlzlddp Experience integrating ML components into wider software systems via APIs or microservices. Experience working with ...

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

Overview We are seeking an AI Engineering Lead to sit at the top of our client’s delivery structure. This role bridges strategic leadership and hands‐on delivery, providing day‐to‐day technical direction to a team of consultants and ensuring high‐quality outcomes across multiple client environments. … operationalisation. Act as the senior technical authority for clients, translating complex concepts into clear defined strategies for senior non‐technical stakeholders. Own solution quality: engineering standards, code reviews, model governance, security, and delivery assurance. Provide technical leadership and coaching; build progression frameworks and mentoring for consultants. Drive pre‐sales ...

possible with our data and handing those proofs to engineering. About the Role: As a Data Scientist at Third Bridge, you will be the engineering-focused prototyping engine within a high-impact data team. Working alongside our senior analytics capability and reporting to the Principal Data Architect, your primary … proof-of-concept (PoC) solutions from new dataset pipelines and ML models to AI-powered internal tools and hand off successful proofs to the engineering team for production integration. You will work with Third Bridge s rich proprietary data assets: transcripts, events, interaction data, commercial performance metrics, and content ...

below overview and requirements for this employment opportunity completely. JOB DESCRIPTION As a Software Engineer II - Applied AI in the AI/ML for Engineering team at JPMorganChase, you'll be at the forefront of AI innovation, combining cutting-edge techniques with unique data assets to optimise business decisions … automate processes. This role offers a unique blend of artificial intelligence and software engineering, allowing you to advance engineering processes and build impactful products. In this role, you will leverage the latest research in Large Language Models, Natural Language Processing and statistical machine learning to build AI-powered ...

implement robust evaluation frameworks to systematically assess and measure the performance of AI agents across key operational metrics. Practice advanced prompt and context engineering (e.g., Chain-of-Thought, ReAct, function calling/tool-use prompts), implement output validation and guardrails to reduce hallucinations. Deploy scalable AI services to cloud … LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion models a plus). Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Strong communication skills for both technical ...

agent tools and APIs to connect agents with external services, databases, and internal systems, ensuring robust output parsing and error handling. Practice advanced prompt engineering and implement output validation and guardrails to reduce hallucinations. Design microservices-based architectures and orchestrate multi-step workflows; instrument agents for tracing, metrics … with agent frameworks such as LangChain, CrewAI, AutoGen, LangGraph. Knowledge of generative models including transformers, GANs, VAEs, and diffusion models. Understanding of data preprocessing, feature engineering, and model/agent evaluation techniques. Familiarity with cloud platforms and containerization technologies. Strong problem-solving skills and ability to work independently ...

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 ...

offer. Job Description About the role: Join us as a Senior Software Engineer in our critical Account Integrity 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 ...

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. ...

understanding of JDBC and database internals. Experience with CI/CD pipelines and Distributed and Concurrent Systems Experience with machine learning basics (data pipelines, feature engineering, recall/precision, familiarity with machine learning systems in production) is a huge plus A strong product mindset and passion for user … work a practical guide DEI @ Wise Wise Tech Stack (2025 update) See what it's like to work at Wise London! Our Engineering career map Wise Engineering do we offer: Starting salary: £87,500 - £111,000 + RSUs Wise Benefits Additional Information For everyone, everywhere. We're people ...

role. Find out more about the daily tasks, overall responsibilities, and required experience for this opportunity by scrolling down now. Senior Analytics Engineer - Analytics Engineering Our story - continued commitment to doing the right thing 2005 seems like a long time ago. Simply Business a small company with … Simply Business. DNA has been central to empowering data-driven decision making at SB. We have invested heavily in our data pipeline, data engineering, business intelligence and machine learning capabilities. The Senior Analytics Engineer is a senior technical role responsible for thedesign and development of robust analytical data models. ...

goals Effective communication and collaboration skills, with demonstrated experience working across cross-functional teams Education Bachelor s degree or higher in Computer Science, Software Engineering, or a related field. Responsibilities As a Software Engineer specializing in AI systems, you will play a key role in designing and implementing production … agents using techniques such as retrieval-augmented generation, prompt optimization, fine-tuning, and reinforcement learning Develop end-to-end pipelines for data ingestion, feature engineering, model inference (batch and real-time), and integration of AI-driven workflows into production systems Collaborate with data scientists and machine learning engineers ...

solutions to help solve business problems. What you'll do Work with the team to carry out analytical projects involving data collection, pre-processing, feature engineering, model development, validation, and deployment. Engage with business stakeholders to understand domain-specific challenges and opportunities, and collaborate during development to ensure … natural language processing, and deep learning. Create clear and compelling visualisations to communicate complex analytical findings effectively. Collaborate with collaborators (including business, product, and engineering) to understand requirements, find opportunities, and provide data-driven recommendations. Collaborate with cross-functional teams to integrate data science solutions into products and services. ...

that reflect risk assessment outcomes and model performance. Qualifications A bit about you: Proven track record of deploying models from scratch, including data preprocessing, feature engineering, model selection, evaluation, and monitoring. Strong Python knowledge. Ability to read through code, especially Java. Demonstrable experience collaborating with engineering ...

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 ...

then scale into production Shape problem definitions with stakeholders in ambiguous environments Bring best practices from adjacent industries into a high-performance setting Data Engineering & Architecture Design/maintain pipelines integrating telemetry/timing, video/image, event operations, and digital/commercial engagement data Develop APIs/services … secure-by-design delivery with cyber teams What we're looking for Essentials 5-10 years' experience in data science/AI/ML engineering Strong Python Production ML deployment experience (end-to-end) Strong SQL + modern data warehouse experience Cloud familiarity + containerisation/orchestration Streaming data ...

expertise to make sense of complex data, working in close collaboration with our business partners. This role will primarily focus on feature engineering and insight generation from new types of data and the development of machine learning models to address critical business challenges in underwriting. … maintain the machine learning models which define our competitive advantage in the financial services market. \n \n Explore and evaluate data, using advanced feature generation and categorisation techniques, in order to stay at the forefront of innovation. \n \n Analyse tabular and non-tabular data, such as text, logs ...

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 ...

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 ...