1 to 25 of 50 Permanent Feature Engineering Jobs in England

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 ❯

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 More ❯

AI solutions across marketing and customer experience. What You'll Do Model & Build: Support the design and deployment of pragmatic machine learning solutions - from feature engineering in SQL to model development in Python, and deploying in production environments like AWS. Explore & Prototype: Help bring new ideas to life … to everything you do. Pace and impact matter here. What You'll Bring Must-Have: A degree in a STEM discipline (Computer Science, Maths, Engineering, etc.) or equivalent practical experience. 2-4 years of experience delivering DS/ML solutions in production environments - ideally in settings where you've … had to wear multiple hats (e.g., startups, small teams). Fluency in Python and SQL; experience building and deploying models end-to-end, from feature engineering to performance validation. Comfort with cloud tools (AWS preferred), Git, and CI/CD pipelines. Ability to work independently and juggle priorities More ❯

support commercial growth and enhance customer experiences and outcomes. Leading and supporting end-to-end data science projects, including business case development, solution design, feature engineering, model development, deployment, and MLOps. Taking ownership of existing ML/AI projects, including ongoing monitoring of model performance, data drift, scoring … support commercial growth and enhance customer experiences and outcomes. Leading and supporting end-to-end data science projects, including business case development, solution design, feature engineering, model development, deployment, and MLOps. Taking ownership of existing ML/AI projects, including ongoing monitoring of model performance, data drift, scoring 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 ❯

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 ❯

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 ❯

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 ❯

PyTorch, or other relevant frameworks. Collaborate with cross-functional teams to integrate AI/ML solutions into our SaaS platform. Work on data preprocessing, feature engineering, and model optimization to ensure high accuracy and performance. Evaluate and fine-tune models to improve accuracy and performance. Integrate machine learning … in AI/ML and fintech trends to drive innovation within the company. Requirements: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Mathematics, or a related field. 3-5 years of professional experience in AI/ML development, preferably in fintech or a related More ❯

PyTorch, or other relevant frameworks. Collaborate with cross-functional teams to integrate AI/ML solutions into our SaaS platform. Work on data preprocessing, feature engineering, and model optimization to ensure high accuracy and performance. Evaluate and fine-tune models to improve accuracy and performance. Integrate machine learning … in AI/ML and fintech trends to drive innovation within the company. Requirements: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Mathematics, or a related field. 3-5 years of professional experience in AI/ML development, preferably in fintech or a related More ❯

PyTorch, or other relevant frameworks. Collaborate with cross-functional teams to integrate AI/ML solutions into our SaaS platform. Work on data preprocessing, feature engineering, and model optimization to ensure high accuracy and performance. Evaluate and fine-tune models to improve accuracy and performance. Integrate machine learning … in AI/ML and fintech trends to drive innovation within the company. Requirements: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Mathematics, or a related field. 3-5 years of professional experience in AI/ML development, preferably in fintech or a related 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 ❯

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 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 ❯

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 ❯

deployment of cutting‐edge algorithmic strategies and quantitative models. The position blends deep hands‐on technical work with high‐level strategic oversight across research, engineering, and trading operations. Key Responsibilities Quantitative Strategy Development & Research Algorithm Design: Lead the creation and refinement of proprietary trading algorithms rooted in the firm … insights. Innovation: Continuously evaluate emerging research (deep learning, reinforcement learning, agent‐based modeling) to sharpen our edge. Technical Infrastructure & Implementation System Architecture: Partner with engineering to design high‐throughput trading systems that scale globally. Software Development: Oversee codebases in Python, C++, Java, or MATLAB; enforce best practices for testing … readable, well‐tested, version‐controlled code and transparent research notebooks. Qualifications Education: B.S. or M.S. in a quantitative field such as Mathematics, Computer Science, Engineering, Statistics, or Physics. Experience: Minimum 5 years building and deploying profitable algorithmic strategies at a hedge fund, bank, or proprietary trading firm. Programming: Advanced More ❯

deployment of cutting‐edge algorithmic strategies and quantitative models. The position blends deep hands‐on technical work with high‐level strategic oversight across research, engineering, and trading operations. Key Responsibilities Quantitative Strategy Development & Research Algorithm Design: Lead the creation and refinement of proprietary trading algorithms rooted in the firm … insights. Innovation: Continuously evaluate emerging research (deep learning, reinforcement learning, agent‐based modeling) to sharpen our edge. Technical Infrastructure & Implementation System Architecture: Partner with engineering to design high‐throughput trading systems that scale globally. Software Development: Oversee codebases in Python, C++, Java, or MATLAB; enforce best practices for testing … readable, well‐tested, version‐controlled code and transparent research notebooks. Qualifications Education: B.S. or M.S. in a quantitative field such as Mathematics, Computer Science, Engineering, Statistics, or Physics. Experience: Minimum 5 years building and deploying profitable algorithmic strategies at a hedge fund, bank, or proprietary trading firm. Programming: Advanced More ❯

deployment of cutting‐edge algorithmic strategies and quantitative models. The position blends deep hands‐on technical work with high‐level strategic oversight across research, engineering, and trading operations. Key Responsibilities Quantitative Strategy Development & Research Algorithm Design: Lead the creation and refinement of proprietary trading algorithms rooted in the firm … insights. Innovation: Continuously evaluate emerging research (deep learning, reinforcement learning, agent‐based modeling) to sharpen our edge. Technical Infrastructure & Implementation System Architecture: Partner with engineering to design high‐throughput trading systems that scale globally. Software Development: Oversee codebases in Python, C++, Java, or MATLAB; enforce best practices for testing … readable, well‐tested, version‐controlled code and transparent research notebooks. Qualifications Education: B.S. or M.S. in a quantitative field such as Mathematics, Computer Science, Engineering, Statistics, or Physics. Experience: Minimum 5 years building and deploying profitable algorithmic strategies at a hedge fund, bank, or proprietary trading firm. Programming: Advanced More ❯

Machine Learning Engineering Manager (Operations) Join to apply for the Machine Learning Engineering Manager (Operations) role at THG Ingenuity . About THG Ingenuity THG Ingenuity is a fully integrated digital commerce ecosystem, designed to power brands without limits. Our global end-to-end tech platform includes three products … of ML projects from conception to deployment and monitoring. Guide the team in building, training, and deploying models. Ensure best practices in data preparation, feature engineering, and model validation. Establish workflows for deployment, monitoring, and scaling of models. Qualifications Proven experience as a Machine Learning Engineer, with leadership More ❯

deliver enterprise-grade data solutions, supporting high-impact business use cases across multiple domains. JOB ACCOUNTABILITIES Define and drive the future direction of data engineering and analytics practices, ensuring alignment with business goals and technological advancements. Design and implement sophisticated data pipelines and transformations, delivering curated, high-quality datasets … documentation and observability of analytical pipelines. Lead collaboration with BI Analysts and Data Scientists to refine methodologies, enhance reporting, and deliver scalable, production-ready feature engineering code. Drive engagement with business stakeholders, effectively communicating complex technical concepts in a clear, accessible manner to align analytics engineering initiatives More ❯

Each team member is approachable and committed to lending a hand, creating an environment where everyone feels supported and valued." - Sreekant, VP of API Engineering The team you'll work with: Reporting to the Director of AI, this is a high-impact role where your expertise will directly shape … Develop, test, deploy, and maintain machine learning models and algorithms, ensuring their scalability, robustness, and performance in production. Data Analysis & Optimization: Conduct data preprocessing, feature engineering, and exploratory analysis to optimize AI/ML models. Pipeline Development & Enhancement: Design, build, and enhance efficient machine learning pipelines, ensuring their … machine learning to identify new opportunities and techniques. To be a successful match you must have: 1+ years in a Machine Learning or ML Engineering role, with hands-on experience in deep learning frameworks (e.g., TensorFlow, PyTorch). Motivated recent graduates are encouraged to apply! A degree in Mathematics More ❯

and innovate on methods like Bayesian neural networks , variational autoencoders , diffusion models , and Gaussian processes for modern AI use cases. Collaborate closely with product, engineering, and business teams to build end-to-end modeling solutions. Conduct deep-dive statistical and machine learning analyses, simulations, and experimental design. Stay current … programming tools. Hands-on experience with classical ML and modern techniques, including deep learning , transformers , diffusion models , and ensemble methods . Solid understanding of feature engineering, dimensionality reduction, model construction, validation, and calibration. Experience with uncertainty quantification and performance estimation (e.g., cross-validation, bootstrapping, Bayesian credible intervals). … Spark, Pandas). Ability to translate ambiguous business problems into structured, measurable, and data-driven approaches. Preferred Qualifications: M.Sc or PhD in Statistics, Electrical Engineering, Computer Science, Physics, or a related field. Background in generative modeling , Bayesian deep learning , signal/image processing , or graph models . Experience applying More ❯