1 to 25 of 239 Feature Engineering Jobs in England

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services … you will be unable to work at home 100% of the time. Your role • Design, develop, and deploy AI/ML models and solutions, including LLMs and GenAI. • Perform feature engineering and selection to optimize model performance. • Select and implement appropriate AI/ML algorithms, including supervised, unsupervised, and reinforcement learning models. • Train, evaluate, and optimize models using More ❯

and translate them into scalable AI/ML and data-driven solutions. Key responsibilities: Design, develop, and deploy AI/ML models and solutions, including LLMs and GenAI. Perform feature engineering and selection to optimize model performance. Select and implement appropriate AI/ML algorithms, including supervised, unsupervised, and reinforcement learning models. Train, evaluate, and optimize models using More ❯

while collaborating with cross-functional teams to shape the future of connectivity. Key responsibilities: Design, develop, and deploy AI/ML models and solutions, including LLMs and GenAI. Perform feature engineering and selection to optimize model performance. Select and implement appropriate AI/ML algorithms, including supervised, unsupervised, and reinforcement learning models. Train, evaluate, and optimize models using More ❯

while collaborating with cross-functional teams to shape the future of connectivity. Key responsibilities: Design, develop, and deploy AI/ML models and solutions, including LLMs and GenAI. Perform feature engineering and selection to optimize model performance. Select and implement appropriate AI/ML algorithms, including supervised, unsupervised, and reinforcement learning models. Train, evaluate, and optimize models using More ❯

to manage model lifecycles. Leverage 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 scalable data pipelines. Model 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 deploying AI solutions at scale. Documentation and Best Practices Document all More ❯

AI/ML team as we scale beyond our seed round. ⸻ Key Responsibilities Architecture & Hands-On Development Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (e.g., neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem … learning models (e.g., CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). … Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark, Kafka). Leadership & Communication: Proven ability to lead cross-functional teams in ambiguous startup settings. Exceptional written and verbal communication skills—able to explain complex concepts to both technical and non-technical stakeholders. Experience recruiting and mentoring engineers More ❯

Description Ciklum is looking for a Principal Data & AI Consultant to join our team full-time in London. We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology … that redefines industries and shapes the way people live. About the role: As a Principal Data & AI Consultant, become a part of a cross-functional development team engineering experiences of tomorrow. Responsibilities: Client engagements, account strategy & delivery responsibility within Data Science or AI Engineering domain(s) Leading client development or enhancement of their Data & AI strategy to align … with Business objectives Ability to support hands on development tasks where necessary/required Technical authority for solution design and development through client engagements Interacts with engineering teams and ensures that solutions meet customer requirements in terms of functionality, performance, availability, scalability, and reliability Senior Stakeholder management Collaborate on commercial development of account(s) with Account Manager & delivery team More ❯

an innovative team shaping next-generation solutions in the Telecoms sector. Key Responsibilities - Design, build and deploy AI/ML models, including LLMs and generative AI - Perform data exploration, feature engineering, and model optimisation - Apply supervised, unsupervised, and reinforcement learning algorithms - Conduct large-scale data analysis across structured and unstructured sources - Develop statistical and predictive models to drive More ❯

and translate them into scalable AI/ML and data-driven solutions. Key responsibilities: Design, develop, and deploy AI/ML models and solutions, including LLMs and GenAI. Perform feature engineering and selection to optimize model performance. Select and implement appropriate AI/ML algorithms, including supervised, unsupervised, and reinforcement learning models. Deploy models to production environments, ensuring … technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure) is desirable. TCS is consistently voted a Top Employer in the UK and globally. Our competitive salary packages feature pension, health care, life assurance, laptop, phone, access to extensive training resources and discounts within the larger Tata network. Diversity, Inclusion and Wellbeing Tata Consultancy Services UK&I is 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 ❯

cutting-edge project, driving innovation through Large Language Models (LLMs), GenAI, and predictive analytics. Key Responsibilities: Design, develop, and deploy AI/ML models, including LLMs and GenAI. Conduct feature engineering, model optimization, and performance tuning. Implement and train supervised, unsupervised, and reinforcement learning models. Carry out advanced data exploration, analysis, and preprocessing. Deploy scalable models into production More ❯

cutting-edge project, driving innovation through Large Language Models (LLMs), GenAI, and predictive analytics. Key Responsibilities: Design, develop, and deploy AI/ML models, including LLMs and GenAI. Conduct feature engineering, model optimization, and performance tuning. Implement and train supervised, unsupervised, and reinforcement learning models. Carry out advanced data exploration, analysis, and preprocessing. Deploy scalable models into production More ❯

cutting-edge project, driving innovation through Large Language Models (LLMs), GenAI, and predictive analytics. Key Responsibilities: Design, develop, and deploy AI/ML models, including LLMs and GenAI. Conduct feature engineering, model optimization, and performance tuning. Implement and train supervised, unsupervised, and reinforcement learning models. Carry out advanced data exploration, analysis, and preprocessing. Deploy scalable models into production More ❯

AI/ML solutions. KEY 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, evaluating, and optimizing models using More ❯

developing and integrating cutting-edge AI solutions-including LLMs and AI agents -into our products and operations at a leading SaaS company. You'll collaborate closely with product and engineering teams to deliver innovative, high-impact systems that push the boundaries of AI in rebate management. This is a highly collaborative and fast-moving environment where your contributions will … or in collaboration with other specialists. Optimize model pipelines for latency, scalability, and cost-efficiency , and support real-time and batch inference needs. Collaborate with MLOps, DevOps, and data engineering teams to ensure reliable model deployment and system integration. Stay informed on current research and emerging tools in LLMs, generative AI, and autonomous agents , and evaluate their practical applicability. … Participate in roadmap planning, design reviews, and documentation to ensure robust and maintainable systems. Required Qualifications 5+ years of experience in machine learning engineering, applied AI, or related fields. Bachelor's or Master's degree in Computer Science, Machine Learning, Engineering , or a related technical discipline. Strong foundation in machine learning and data science fundamentals -including supervised/ More ❯

developing and integrating cutting-edge AI solutions—including LLMs and AI agents —into our products and operations at a leading SaaS company. You’ll collaborate closely with product and engineering teams to deliver innovative, high-impact systems that push the boundaries of AI in rebate management. This is a highly collaborative and fast-moving environment where your contributions will … or in collaboration with other specialists. Optimize model pipelines for latency, scalability, and cost-efficiency, and support real-time and batch inference needs. Collaborate with MLOps, DevOps, and data engineering teams to ensure reliable model deployment and system integration. Stay informed on current research and emerging tools in LLMs, generative AI, and autonomous agents, and evaluate their practical applicability. … Participate in roadmap planning, design reviews, and documentation to ensure robust and maintainable systems. Required Qualifications 5+ years of experience in machine learning engineering, applied AI, or related fields. Bachelor’s or Master’s degree in Computer Science, Machine Learning, Engineering, or a related technical discipline. Strong foundation in machine learning and data science fundamentals—including supervised/ More ❯

infrastructure (e.g., connected buildings, utilities) or industrial automation (e.g., SCADA, PLC systems, Industry 4.0). They should have a strong understanding of how to apply data science and data engineering techniques to develop, validate, and enhance AI/ML models within these complex and data-rich environments. Job Description Essential Responsibilities: Design and conduct experiments to test and validate … results, insights, and recommendations clearly to stakeholders, including product managers and leadership teams. Must-Have Requirements PhD, Master’s, or Bachelor’s degree in Data Science, Computer Science, Electrical Engineering, or a related field with hands-on experience in model validation. Significant experience working in the energy sector, particularly in energy systems, grid automation, or smart grid technologies. Solid … knowledge of statistical techniques, model performance metrics, and validation methodologies for AI/ML models. Proficiency in programming languages such as Python, R, or MATLAB. Experience with data wrangling, feature engineering, and preparing datasets for model validation. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and model evaluation techniques. Experience with cloud platforms (e.g., AWS, Azure More ❯

AI. The team includes data strategists, consultants, data scientists and analysts that work alongside DEPT teams around the world across different services – from commerce, to full-funnel media, content engineering to internal operations. You will be solving some of the hardest and most challenging problems facing some of the best loved brands in the world – and doing this alongside … machine learning models for marketing attribution, customer prediction, segmentation, and recommendation systems with deep understanding of customer experience and marketing use-cases Implement end-to-end ML pipelines including feature engineering, model training, deployment, and monitoring Perform advanced statistical analysis including A/B testing, causal inference, and experimental design Deploy production ML systems with automated retraining, drift … on data and ML implementation, serving as a trusted advisor on data-driven decision making WHAT WE ARE LOOKING FOR MSc degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field 3+ years of experience in data science and/or ML engineering roles Strong foundation in statistics and mathematics including probability theory, hypothesis More ❯

Build interactive front-ends (Tableau, Streamlit, Plotly Dash) so non-technical users can explore results intuitively Turn insights into actionable recommendations and present findings to clients; Contribute reusable components (feature engineering blocks, forecasting engines, GenAI pipelines) to our internal AI/ML toolkit Support business-development by shaping analytics in proposals and thought-leadership Tech you'll use … to pick up new languages and frameworks quickly. What we're looking for Degree (2:1 or above) or Master's in a quantitative field (Data Science, Computer Science, Engineering, Mathematics, Physics, Economics etc.) 0-2 yrs experience applying Python/SQL & core ML to real-world data sets Confidence explaining technical concepts to senior business audiences Intellectual curiosity More ❯

models for image classification problems Collaborate with a co-located team of Software Engineers to ensure seamless integration of models into production environments. Conduct exploratory data analysis, data preprocessing, feature engineering to uncover insights and guide model development. Stay up-to-date with the latest advancements in deep learning and AI technologies and apply them to real-world More ❯

and technologies that you can 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 systems (e.g., Git). • Familiarity … ML): • Deep understanding of machine 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, tracking, and model monitoring. • Ability … as an MLOps Engineer or 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/ML systems. Technical Insight Skills More ❯

and technologies that you can 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 systems (e.g., Git). Familiarity … ML): Deep understanding of machine 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, tracking, and model monitoring. Ability … as an MLOps Engineer or 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/ML systems. Technical Insight Skills More ❯

metadata enrichment strategies to enhance data utility and accessibility for AI systems. Algorithm Implementation & Optimization: Implement and optimize state-of-the-art algorithms and pipelines for efficient data processing, feature engineering, and data transformation tailored for LLM and GenAI applications. GenAI Application Development: Apply and integrate frameworks like LangChain and Hugging Face Transformers to build modular, scalable, and … robust Generative AI data pipelines and applications. Prompt Engineering Application: Apply advanced prompt engineering techniques to optimize LLM performance for specific data extraction, summarization, and generation tasks, working closely. LLM Evaluation Support: Contribute to the systematic evaluation of Large Language Models (LLMs) outputs, analysing quality, relevance, and accuracy, and supporting the implementation of LLM-as-a-judge frameworks. … systems, including working with embedding models, vector databases, and, where applicable, knowledge graphs, to enhance data retrieval for GenAI. Cross-Functional Collaboration: Collaborate effectively with global data science teams, engineering, and product stakeholders to integrate data solutions and ensure alignment with broader company objectives. Operational Excellence: Troubleshoot and resolve data-related issues promptly to minimize potential disruptions, ensuring high More ❯

and technologies that you can 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 systems (e.g., Git). • Familiarity … ML): • Deep understanding of machine 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, tracking, and model monitoring. • Ability … as an MLOps Engineer or 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/ML systems. Technical Insight • Skills More ❯

features. Company Description Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change. By combining world-class engineering, industry expertise, and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and … expertise in Python-based AI/ML development, big data processing, and cloud-based AI platforms (Databricks, Azure ML, AWS SageMaker, GCP Vertex AI). Key Responsibilities Data Exploration & Feature Engineering Perform thorough Exploratory Data Analysis (EDA) and identify key variables, patterns, and anomalies. Engineer and select features for optimal model performance, leveraging domain understanding. Machine Learning & Statistical … skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know. Seniority level Mid-Senior level Employment type Full-time Job function Engineering and Information Technology Industries IT Services and IT Consulting #J-18808-Ljbffr More ❯