1 to 25 of 84 Feature Engineering Jobs in England

practices, serving as a data engineer/machine learning engineer in a technology development and delivery capacity. With your expertise in computer science, computer engineering, cloud, and data transformation (ETL & feature engineering), you will help build and shape McKinsey's scientific AI offering. As a member of … assets, and building the firm's reputation in your area of expertise. Your Impact You will leverage your expertise in data/machine learning engineering and product development to address complex client problems through part-time staffing, support the development of engineering roadmaps for cell-level initiatives, and … AI prototypes into deployment-ready solutions. By working directly with client delivery teams, you will ensure seamless implementation of these solutions. You will translate engineering concepts and design decisions for senior stakeholders, write optimized code to enhance McKinsey's AI Toolbox, and codify methodologies for future deployment. Collaborating with More ❯

analysis, statistical models, machine learning) using modern data science tools (Notebooks, Clouds). Design and implementation of machine learning models, metrics, and application of feature engineering techniques applied to customer problems. Support pre-sales in business opportunities and the engineering teams in the implementation of production-ready … models to help test hypotheses. Communicate findings effectively to an audience of engineers and executives. Required Qualifications: Bachelor's Degree in Computer Science/Engineering, Applied Math, Statistics, Physics or other related quantitative areas. Advanced oral and written communication skills in English. Ability to understand mathematical models and algorithms … use of the best frameworks for machine learning pipelines, data visualization, manipulation and transforming, models training and evaluation, and models deployment. Experience with common feature engineering techniques and machine learning algorithms for Supervised and Unsupervised Learning. Experience with Natural Language Processing (NLP and NLU). Experience using Generative More ❯

analysis, statistical models, machine learning) using modern data science tools (Notebooks, Clouds). Design and implementation of machine learning models, metrics, and application of feature engineering techniques applied to customer problems. Support pre-sales in business opportunities and the engineering teams in the implementation of production-ready … models to help test hypotheses. Communicate findings effectively to an audience of engineers and executives. Required Qualifications: Bachelor’s Degree in Computer Science/Engineering, Applied Math, Statistics, Physics or other related quantitative areas. Advanced oral and written communication skills in English. Ability to understand mathematical models and algorithms … use of the best frameworks for machine learning pipelines, data visualization, manipulation and transforming, models training and evaluation, and models deployment. Experience with common feature engineering techniques and machine learning algorithms for Supervised and Unsupervised Learning. Experience with Natural Language Processing (NLP and NLU). Experience using Generative More ❯

analysis, statistical models, machine learning) using modern data science tools (Notebooks, Cloud platforms). Design and implement machine learning models, develop metrics, and apply feature engineering techniques tailored to customer problems. Support pre-sales efforts and assist engineering teams in deploying production-ready machine learning solutions. Evaluate … segmentation, using machine learning models to test hypotheses. Communicate findings effectively to engineers and executives. Required Qualifications: Bachelor's Degree in Computer Science/Engineering, Applied Math, Statistics, Physics, or related quantitative fields. Proficiency in English, both oral and written. Ability to understand and implement mathematical models and algorithms … visible progress updates to the team. Proficiency in Python or R, SQL, and relevant frameworks for machine learning, data visualization, and deployment. Experience with feature engineering and machine learning algorithms for Supervised and Unsupervised Learning (Regression, Classification, Clustering, etc.). Experience with Natural Language Processing (NLP and NLU More ❯

analysis, statistical models, machine learning) using modern data science tools (Notebooks, Cloud platforms). Design and implement machine learning models, develop metrics, and apply feature engineering techniques tailored to customer problems. Support pre-sales efforts and assist engineering teams in deploying production-ready machine learning solutions. Evaluate … segmentation, using machine learning models to test hypotheses. Communicate findings effectively to engineers and executives. Required Qualifications: Bachelor’s Degree in Computer Science/Engineering, Applied Math, Statistics, Physics, or related quantitative fields. Proficiency in English, both oral and written. Ability to understand and implement mathematical models and algorithms … visible progress updates to the team. Proficiency in Python or R, SQL, and relevant frameworks for machine learning, data visualization, and deployment. Experience with feature engineering and machine learning algorithms for Supervised and Unsupervised Learning (Regression, Classification, Clustering, etc.). Experience with Natural Language Processing (NLP and NLU More ❯

learning systems at scale that drive measurable impact for our business Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance Partner with stakeholders to propose innovative data products that leverage Trainline … Flow Have experience with agile delivery methodologies and CI/CD processes and tools Have a broad understanding of data extraction, data manipulation and feature engineering techniques Are familiar with statistical methodologies. Have good communication skills Nice to have Experience with LangGraph or LangChain Experience with transport industry More ❯

learning systems at scale that drive measurable impact for our business Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance Partner with stakeholders to propose innovative data products that leverage Trainline … Flow Have experience with agile delivery methodologies and CI/CD processes and tools Have a broad understanding of data extraction, data manipulation and feature engineering techniques Are familiar with statistical methodologies. Have good communication skills Nice to have Experience with LangGraph or LangChain Experience with transport industry More ❯

real-world problems, shipping results fast, all whilst meeting launch deadlines. Take ownership of end-to-end ML model development—from data preprocessing and feature engineering to training, testing, and deployment. Collaborate across teams to implement machine learning solutions into production systems, ensuring that models are scalable, reliable … machine learning, with a strong understanding of core ML algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Hands-on experience with data preprocessing, feature engineering, and model training for real-world problems. Strong Python and Java programming skills and familiarity with NLP algorithms and libraries. Solid understanding … London, England, United Kingdom 2 weeks ago Research Engineer, ML, AI & Computer Vision London, England, United Kingdom 2 weeks ago Machine Learning and AI Engineering Lead We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J More ❯

real-world problems, shipping results fast, all whilst meeting launch deadlines. Take ownership of end-to-end ML model development-from data preprocessing and feature engineering to training, testing, and deployment. Collaborate across teams to implement machine learning solutions into production systems, ensuring that models are scalable, reliable … machine learning, with a strong understanding of core ML algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Hands-on experience with data preprocessing, feature engineering, and model training for real-world problems. Strong Python and Java programming skills and familiarity with NLP algorithms and libraries. Solid understanding More ❯

cloud platforms like Azure, AWS, and GCP for scalable ML model deployment. Employ frameworks like TensorFlow, PyTorch, and scikit-learn for model development. Data Engineering and Preparation Oversee data ingestion, cleaning, transformation, and feature engineering processes to ensure high-quality datasets. Work with large datasets and implement … Evaluation and Optimization Evaluate model performance using metrics such as R2, RMSE, ROC-AUC, F1 score, and precision-recall. Optimize models through hyperparameter tuning, feature selection, and iterative testing. Collaboration and Deployment Partner with cross-functional teams to integrate ML solutions into business applications. Build and maintain APIs for More ❯

will be headquartered at our Westminster, Colorado offices and is primarily an on-premises position. The Machine Learning Engineer will work closely with an engineering team composed primarily of aerospace and software engineers. The ideal candidate has a strong background in software development best practices, mathematics, and statistics, as … and implement state-of-the-art machine learning algorithms and techniques Design, develop, and deploy machine learning models and systems that can address various engineering problems and opportunities Perform data analysis, preprocessing, feature engineering, and model evaluation Optimize the performance, scalability, and reliability of machine learning solutions … of hands-on professional experience. Master's degree or PhD research may contribute to this experience. Bachelor's degree or higher in Computer Science, Engineering, Mathematics, Statistics, or related field Proficient with one or more machine learning model development frameworks, especially PyTorch or TensorFlow. Familiar with the basics of More ❯

the heart of Central London and home to our Research Lab. The role We are seeking exceptional Engineers to join our newly established GenAI Engineering team. In this role, you will be at the forefront of developing and implementing cutting-edge AI solutions across G-Research, working on a … wide range of projects. As a key member of the GenAI Engineering team, you will collaborate with researchers, data scientists and business stakeholders to design, develop and deploy AI applications that drive innovation and efficiency throughout the organisation. Key responsibilities of the role include: Developing end-to-end AI … Who are we looking for? We are seeking candidates who are comfortable working both independently and in small teams on a variety of AI engineering challenges, with a focus on practical implementation and deployment of AI solutions. You will have the opportunity to work on diverse and challenging AI More ❯

the heart of Central London and home to our Research Lab. The role We are seeking exceptional Engineers to join our newly established GenAI Engineering team. In this role, you will be at the forefront of developing and implementing cutting-edge AI solutions across G-Research, working on a … wide range of projects. As a key member of the GenAI Engineering team, you will collaborate with researchers, data scientists and business stakeholders to design, develop and deploy AI applications that drive innovation and efficiency throughout the organisation. Key responsibilities of the role include: Developing end-to-end AI … Who are we looking for? We are seeking candidates who are comfortable working both independently and in small teams on a variety of AI engineering challenges, with a focus on practical implementation and deployment of AI solutions. You will have the opportunity to work on diverse and challenging AI More ❯

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 … 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 … 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 More ❯

RESPONSIBILITIES: In this role, you will be responsible for: Designing, developing, and deploying AI/ML models and solutions, including LLMs and GenAI. Performing feature engineering and selection to optimize model performance. Selecting and implementing appropriate AI/ML algorithms, including supervised, unsupervised, and reinforcement learning models. Training More ❯

teams to understand business requirements and deliver data-driven insights. Design and build scalable data pipelines and ETL processes. Perform data exploration, preprocessing, and feature engineering. Conduct statistical analysis and machine learning model development. Communicate findings and insights to stakeholders through data visualization and reports. Stay current with industry More ❯

then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: • Proficiency in programming languages used in ML, such as Python/Java. • Knowledge of software development best practices and methodologies. • Experience with version control … learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and microservices. • Familiarity with ML lifecycle management, including versioning … in a similar role, with an excellent understanding of AI/ML lifecycle management. Strong experience deploying and productionising ML models. Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies. Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ More ❯

fine-tuning, and prompt engineering. ✅ Proficiency in programming languages such as Python, R, and Java. (Python is a must have!) ✅ Strong knowledge of data engineering processes (data cleaning, feature engineering, and integration). ✅ Ability to work independently and as part of a dynamic team. ✅ Experience with Microsoft More ❯

then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: Proficiency in programming languages used in ML, such as Python/Java. Knowledge of software development best practices and methodologies. Experience with version control … learning principles, algorithms, and techniques. Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proficiency in data preprocessing, feature engineering, and model evaluation. Knowledge of ML model deployment and serving strategies, including containerization and microservices. Familiarity with ML lifecycle management, including versioning … in a similar role, with an excellent understanding of AI/ML lifecycle management. Strong experience deploying and productionising ML models. Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies. Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ More ❯

then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: Proficiency in programming languages used in ML, such as Python/Java. Knowledge of software development best practices and methodologies. Experience with version control … learning principles, algorithms, and techniques. Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proficiency in data preprocessing, feature engineering, and model evaluation. Knowledge of ML model deployment and serving strategies, including containerization and microservices. Familiarity with ML lifecycle management, including versioning … in a similar role, with an excellent understanding of AI/ML lifecycle management. Strong experience deploying and productionising ML models. Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies. Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ More ❯

then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: • Proficiency in programming languages used in ML, such as Python/Java. • Knowledge of software development best practices and methodologies. • Experience with version control … learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and microservices. • Familiarity with ML lifecycle management, including versioning … in a similar role, with an excellent understanding of AI/ML lifecycle management. • Strong experience deploying and productionizing ML models. • Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies. • Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ More ❯

then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: • Proficiency in programming languages used in ML, such as Python/Java. • Knowledge of software development best practices and methodologies. • Experience with version control … learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and microservices. • Familiarity with ML lifecycle management, including versioning … in a similar role, with an excellent understanding of AI/ML lifecycle management. • Strong experience deploying and productionizing ML models. • Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies. • Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ More ❯

specialists and external data suppliers. Please see full Job Description and Person Specification. Person Specification Knowledge and Experience Practical application expertise of managing data engineering projects and processes including data wrangling methods, models, data structures, and data formats such as JSON, XML and XSD. Machine learning for engineering … with relational SQL and databases. Experience with Azure tech stack such as Fabric, Data Factory, Synapse Analytics, Databricks and Lakehouses. Experience in building data engineering projects in Fabric. Knowledge of data warehousing and modelling concepts such as CDC/SCD. Ability to troubleshoot and solve numerical and technical problems. … complex organisation. Recent and ongoing continuous professional and personal development action and activity. Planning, objective setting and experience of performance management that incorporates Data Engineering and Data Science. Knowledge of Data Protection, legislation and directions that support the provision of data for counter fraud purposes. Experience in project delivery More ❯

innovation and leadership, this is the role you’ve been waiting for. Join a fast-growing Tech for Good Marketplace as their new ML Engineering Leader , where you’ll be at the forefront of AI-driven product development, building a skilled team, and driving the ML | Data Science | AI … vision for the business. What You'll Do: Develop and lead the ML Engineering | AI strategy as the company looks to drive a new period of experimentation & innovation with a personalised customer experience at the forefront of their plans. Lead and grow a team of ML engineers, fostering a … with software engineers, product managers, and business teams to define ML-driven solutions. Stay up-to-date with advancements in ML, AI, and data engineering best practices. Drive best practices in model explainability, bias mitigation, and ethical AI principles. What We’re Looking For: 5+ years of experience in More ❯

NLP tasks. Relationship Extraction: Evaluating different models for use-case specific RE, such as ATG. Document and text Classification Data Science: Data clustering algorithms, feature engineering Evaluate and integrate new technologies and models. Cross-team collaboration, identifying innovations and architecting solutions. Provide leadership and technical direction to various More ❯