1 to 25 of 36 Remote Feature Engineering Jobs in the UK

Engineering Manager, Machine Learning Platform London We're on a mission to make money work for everyone. We're waving goodbye to the complicated and confusing ways of traditional banking. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history … solve problems and change lives through Monzo ️ London or Remote (UK) Base salary for this role is £110,500 - £145,000 (depending on experience) + stock options + Benefits Engineering Manager, Machine Learning Platform Engineering Management at Monzo: Engineering Managers at Monzo are part of cross-functional, autonomous teams and groups. Our teams are mission driven, and … groups, and then collectives - we aim to keep our line management structure as shallow as possible, and for teams to directly own decision making relevant to their work. The Engineering Manager role at Monzo is split into three pillars - people, product, and technical leadership. Engineering Managers are accountable for the technical and delivery outcomes for their area - that More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

and methodologies to continually improve solution offerings. Provide expertise and guidance on AI best practices, contributing to the organization's AI strategy and innovation efforts. Conduct data analysis and feature engineering to prepare data for use in AI models, utilizing Azure Data Lake Develop robust testing and validation processes to ensure the accuracy and reliability of AI models … AI solutions, including Azure OpenAI Service, Azure Cognitive Services, and Azure Machine Learning. Familiarity with Azure Databricks is a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large datasets, experience with Azure Data Factory, Azure SQL Database … Azure networking and security services tailored for AI applications. Excellent communication and teamwork skills, with experience working in agile development environments. Qualifications University degree in computer science or software engineering and/or 5+ years equivalent work experience within a cloud environment. Cloud Certifications desirable Qualifications such as the following desirable: Microsoft Azure AI Engineer Fundamentals/Associate Microsoft More ❯

and methodologies to continually improve solution offerings. Provide expertise and guidance on AI best practices, contributing to the organization's AI strategy and innovation efforts. Conduct data analysis and feature engineering to prepare data for use in AI models, utilizing Azure Data Lake Develop robust testing and validation processes to ensure the accuracy and reliability of AI models … AI solutions, including Azure OpenAI Service, Azure Cognitive Services, and Azure Machine Learning. Familiarity with Azure Databricks is a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large datasets, experience with Azure Data Factory, Azure SQL Database … Azure networking and security services tailored for AI applications. Excellent communication and teamwork skills, with experience working in agile development environments. Qualifications University degree in computer science or software engineering and/or 5+ years equivalent work experience within a cloud environment. Cloud Certifications desirable Qualifications such as the following desirable: Microsoft Azure AI Engineer Fundamentals/Associate Microsoft More ❯

plays a crucial role in this journey, working on cutting-edge projects that enhance our digital presence and improve customer engagement. As a Senior AI Engineer within the Technology Engineering team in CIO, you will play a pivotal role in designing, developing, and deploying AI and machine learning solutions that address real-world business challenges. You will work closely … with cross-functional teams-including Data Science, Engineering, Product, and Business stakeholders-to identify opportunities for AI innovation and deliver scalable, ethical, and high-impact solutions. You will contribute to the Centre of Excellence for AI Engineering, support the adoption of GenAIOps practices, and help embed responsible AI principles across the development lifecycle. You'll also mentor junior … engineers, promote reusability of AI components, and support the continuous improvement of AI engineering practices across the organisation. Skills we would love you to have: Experience in AI/ML engineering or applied machine learning. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. More ❯

Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. This position is within our decision sciences practice which focuses on delivering solutions via machine learning and statistical modelling. What you will do As a part of Aimpoint … Become a trusted advisor working with clients to design end-to-end analytical solutions Work independently to solve complex data science use-cases across various industries Design and develop feature engineering pipelines, build ML & AI infrastructure, deploy models, and orchestrate advanced analytical insights Write code in SQL, Python, and Spark following software engineering best practices Collaborate with … impact for your clients and do so through thoughtfulness, prioritization, and seeing a solution through from brainstorming to deployment. In particular you have these traits: Degree in Computer Science, Engineering, Mathematics, or equivalent experience. Experience with building high quality Data Science models to solve a client's business problems Experience with managing stakeholders and collaborating with customers Strong written More ❯

and visibility functionality. As a senior member of the team, you'll be self motivated and be able to take ownership of projects, collaborate closely with stakeholders across product, engineering, and business to deliver data science solutions. Responsibilities Work across and support a range of data use cases including analytics and data provisioning Lead the design, development, and deployment … models and advanced analytics solutions to support recommendation and insight to production use cases Apply statistical techniques to extract insights and support data-driven decision-making Work alongside data engineering in requirements for data pipelines and feature engineering Promote best practices in data science, model validation, documentation, and reproducibility Qualifications Experience Strong coding skills in Python, including More ❯

ll Bring: We are seeking a seasoned professional who is excited by the unique challenges of AI data. Qualifications What are we looking for? Must-Have Skills: Extensive Data Engineering Experience: Proven track record (3+ years) in designing, building, and maintaining large-scale data pipelines and data warehousing solutions. Cloud Platform Mastery: Expert-level proficiency with at least one … data technologies like Apache Spark, Kafka, and data orchestration tools such as Apache Airflow or Prefect. ML Data Acumen: Solid understanding of data requirements for machine learning models, including feature engineering, data validation, and dataset versioning. Vector Database Experience: Practical experience working with vector databases (e.g., Pinecone, Milvus, Chroma) for embedding storage and retrieval. Generative AI Familiarity: Understanding … TensorFlow for data preparation in an ML context. Experience with real-time data streaming architectures. Familiarity with containerization (Docker, Kubernetes). Master's or Ph.D. in Computer Science, Data Engineering, or a related quantitative field. Additional Information Starcom has fantastic benefits on offer to all of our employees. In addition to the classics,Pension,Life Assurance, Private Medical and More ❯

platforms (GCP preferred, AWS and Azure acceptable) Familiarity with Python ML packages such as PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas Strong SQL skills for data preparation and feature engineering Knowledge of MLOps principles, including automated retraining, monitoring, and deployment strategies Basic understanding of containerization and tools like Docker Nice-to-have skills: Experience with Google Cloud More ❯

Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc. * Strong knowledge of SQL and its use for data preparation & feature engineering * Understanding of & practical experience with implementing MLOps principals - including automated model retraining, monitoring & deployment strategies * Some knowledge of containerisation & use of tools like Docker & Docker Compose Nice More ❯

machine learning and deep learning models. Contribute to scalable and reusable data pipelines using modern ML workflows. Conduct experiments and benchmarking exercises to test model performance. Perform error analysis, feature importance, and other model diagnostics. Track and log training/testing outcomes to support reproducibility and model versioning. Engineering Contributions Help build and integrate AI-powered APIs, scripts … tools, and containerization (e.g., Docker) to maintain codebase quality. Applied AI Domains Work on projects involving Natural Language Processing (NLP), Computer Vision, Generative AI, or Recommendation Systems. Support annotation, feature engineering, and augmentation tasks where necessary. Write clear, well-organized documentation for code, models, datasets, and workflows. Participate in team meetings, sprint planning, and code reviews. Engage with … to reflect on progress, set learning goals, and track outcomes. Required Qualifications A Bachelor's or Master's degree (completed or ongoing) in Computer Science, Data Science, Mathematics, Software Engineering, or a related STEM field. Eligibility to enroll in a Level 6 or Level 7 AI/ML/Data Science apprenticeship programme. Core Skills & Competencies Technical Skills Programming More ❯

Domain: Automotive Job Type: Permanent/Contract Location: Onsite in West Midlands, UK/Remote The ideal candidate brings hands-on experience in machine learning model development, integration with engineering simulations, and practical application to propulsion system delivery. You will be responsible for creating advanced digital tools that accelerate and enhance the performance, accuracy, and efficiency of propulsion system … Python, including ML libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, etc. Expert Level in programming such as VBA, Python, JAVA and other coding tools. Familiarity with data processing, feature engineering, and model evaluation techniques. Soft Skills: Strong analytical and creative thinking skills to apply AI in complex engineering contexts. Excellent communication skills for cross-functional collaboration … and presenting technical results. Initiative-driven with a passion for innovation and digital transformation. Education: Bachelor's or Master's degree in Mechanical Engineering, Computer Science, Data Science, Mechatronics, or a related field. Additional certifications or training in AI/ML or Data Engineering are highly desirable What we offer (For Permanent) Competitive Salary in line with level More ❯

and gain exposure to a wide range of tools, including cloud-based AI/ML platforms. What you'll do: Support development and optimisation of ML models through EDA, feature engineering, and testing Assist with data labelling, wrangling, validation, and governance Collaborate with stakeholders to deliver analytical insights and AI-driven solutions Use Python, SQL, and cloud-based More ❯

the organization. Essential Duties Understand business problems and conduct statistical analysis independently. Break down hard problems. Communicate effectively to senior stakeholders. Deliver value end-to-end. Self-serve data engineering and infrastructure as required. Make recommendations on best practice in terms of analysis, machine learning and data science. Have a transformative presence in the team. Develop and implement machine … learning models, including feature engineering, model design, training, and deployment. Perform data mining, exploration, and statistical analysis to uncover trends and actionable insights. Create data visualizations, reports, dashboards, and perform data audits. Leverage predictive models to optimize customer experiences and drive business outcomes. Create automated anomaly detection systems to monitor and ensure data quality and operational performance. Desired … Computer Science, or a related field. D. in a quantitative field such as Statistics, Computer Science, Mathematics, or Engineering. A "full stack" data scientist - with extensive expertise of data engineering, analysis and analytics, as well as machine learning. 6+ years of experience working in Data Science, preferably within a Software organization. Experience with financial fraud detection and prevention is More ❯

well as: Bachelor’s or master’s degree in computer science, Artificial Intelligence, Machine Learning, or a related field (desirable). Strong understanding of data structures, algorithms, and software engineering principles. Familiarity with data preprocessing, feature engineering, and model evaluation techniques. Familiarity with AI, machine learning, or blockchain technologies. Excellent communication, and problem-solving skills. Understanding of More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

at scale to help optimise product bidding and maximise profit across platforms like Google Shopping. Expect to work across the full ML lifecycle-from exploring large, messy datasets and engineering features, to evaluating models offline and running experiments to validate impact. At the same time, you'll build, deploy and monitor models in production: setting up retraining workflows, pipeline … clean, documented, well tested and reviewed code and have tooling and a culture to support this. This is a hands-on, high-impact role that blends research, experimentation and engineering, all tied to clear business outcomes. You'll collaborate closely with marketers, data analysts and engineers, and play a key part in shaping the future of how we scale … impact ad quality or model input 3+ years of experience building and deploying ML models in production Strong Python and SQL skills, with a solid understanding of data wrangling, feature engineering and model evaluation Deep understanding of the data science process-comfortable with exploratory analysis, statistical testing, and model comparison techniques Experience with structured prediction problems (e.g. regression More ❯

datasets (e.g. genomic sequences, patient records, imaging) Collaborate with bioinformaticians and clinical researchers to translate data into actionable insights Contribute to the development of internal tools for data preprocessing , feature engineering , and model evaluation Requirements: 3+ years of experience in data science or ML, ideally in biotech or healthcare Strong Python programming skills and experience with ML libraries More ❯

environment (AWS, GCP or Azure) Collaborate with data engineers, analysts, and product teams to translate business needs into AI-driven solutions Contribute to the development of data pipelines and feature engineering workflows Integrate models into production using APIs, batch jobs, or real-time systems Apply best practices around experimentation, evaluation, versioning, and monitoring Contribute to documentation, knowledge sharing More ❯

drive innovation into the product development process. You will interpret your client’s objectives, desires, and preferences to help the wider technical team understand the opportunities and apply data engineering responsibilities consistently. You will be working on an interesting range of projects that deliver to National Security customers and as such, you will have to hold the highest level … of UK Security Vetting (DV), upon application. Key Responsibilities: You will blend Data Engineering and Data Science, and will have experience that might cover a number of the tasks listed below: Data Engineering tasks Manage the implementation and development of integrations between the data warehouse and other systems. Create deployable data pipelines that are tested and robust using … Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. Review the execution of software solutions and how these perform for the business and your clients, establishing More ❯

drive innovation into the product development process. You will interpret your client’s objectives, desires, and preferences to help the wider technical team understand the opportunities and apply data engineering responsibilities consistently. You will be working on an interesting range of projects that deliver to National Security customers and as such, you will have to hold the highest level … of UK Security Vetting (DV), upon application. Key Responsibilities: You will blend Data Engineering and Data Science, and will have experience that might cover a number of the tasks listed below: Data Engineering tasks Manage the implementation and development of integrations between the data warehouse and other systems. Create deployable data pipelines that are tested and robust using … Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. Review the execution of software solutions and how these perform for the business and your clients, establishing More ❯