51 to 75 of 140 Feature Engineering Jobs in London

innovation and transformation goals through GenAI/ML architectures. This role requires technologists with deep domain-specific expertise, able to address advanced concepts and feature designs. As part of the AGS organization, SSAs work with customers who have complex requirements that require expert-level knowledge to solve. You must … recommendation systems, or conversational AI.Ideally, you also have experience with large language models (LLMs), foundation models, retrieval-augmented generation (RAG), fine-tuning, prompt engineering, or agentic AI architectures. Hands-on experience with AWS AI/ML services such as Amazon Bedrock, Amazon SageMaker, Amazon Q, or Amazon Rekognition ...

that turn real customer signals into timely actions and measurable outcomes allowing customers to amplify consumer voice for LLM visibility advantage. Partner across Product, Engineering, CS, and Commercial to make the human signal visible, actionable, and compounding in the product. Establish experimentation and measurement foundations: design how we test … into simple, trusted narratives that guide product and commercial decisions. Productionize and scale thoughtfully: ship durable data and model workflows in collaboration with the engineering team, ensure quality and monitoring, and document decisions so the system is reliable, explainable, and easy to evolve. What you’ll bring Track record ...

statistical techniques to uncover behaviour, patterns and commercial opportunity. Design rigorous experiments and measurement approaches that reveal genuine incremental impact. Set best practice in feature engineering, validation, reproducibility and model evaluation. Work with Data Engineering to productionise high-value analytical solutions. Guide model monitoring, drift management ...

full delivery lifecycle, from early ideas through to production systems that create measurable impact for our customers and the business. As MLOps Engineering Manager, you will help shape how we build, deploy and operate machine learning products at scale, working closely with ML Engineers, Data Engineers, Software Engineers, Data … operation of machine learning products, ensuring models and AI systems are production‐ready, observable and able to support Trainline’s growth. Partner closely with engineering, data science, product and data teams to bring strong engineering standards into machine learning delivery, while recognising the specific challenges of data ...

Your Impact Customer Onboarding & Engine Customization: Lead the technical deployment of our engines for new clients. Partner closely with customers, Customer Success, Product, and Engineering to adapt and customize ML models, ensuring they accurately reflect client-specific business logic, operational guardrails, and unique data nuances. Analytic Engine Development: Design … implement robust Machine Learning (LightGBM, XGBoost) and Deep Learning (PyTorch) models specifically focused on complex demand sensing and resolving cold-start forecasting problems. Feature Engineering Pipelines: Build and optimize scalable data pipelines leveraging a hybrid SQL/Python architecture (dbt, Snowflake) to extract rich, localized temporal signals from ...

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 ...

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 ...

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 ...

/ML, including leading teams and projects from conception to production Strong foundation in AI/ML concepts and practical experience with data analysis, feature engineering, and model development Experience working with large, complex datasets and applying statistical analysis Hands‐on experience training, deploying, and maintaining machine learning ...

world usage. Own ML projects end to end within a product team, including framing the problem, choosing the approach, executing the plan, shipping the feature, and monitoring its performance in production. Work closely with SMB, Scaler, or Enterprise product teams on focused ML problems tied to clear customer … organization. Own ML projects end to end within a product team, including framing the problem, choosing the approach, executing the plan, shipping the feature, and monitoring its performance in production. Work closely with SMB, Scaler, or Enterprise product teams on focused ML problems tied to clear customer and business ...

logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling ...

logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling ...

grow and advance. Accenture's Data and AI practice covers the range of Data and AI skills, from Strategy, Data Science, Data Architecture, AI Engineering and Visual Insights. When combined with Accenture's broader Strategy and Consulting practice, we are able to bring together the unique ability to drive … capabilities that empower analytics and AI teams. Assist senior leaders in shaping elements of the strategic direction for practice's data science and data engineering ecosystem. Help assess generative AI proposals by reviewing feasibility, data requirements, model considerations, and integration with existing technology stacks. Collaborate with digital teams, architects ...

cross-functional teams, driving technical deployments, and managing stakeholders. Preferred qualifications Experience in systems design with the ability to explain model architectures, data analysis, feature engineering, and agent design patterns. Experience in business-aligned evaluation design to define metrics, collect data, and measure a program's effectiveness … impact. Experience in process reimagination, assessing legacy workflows, and designing automated, AI-driven alternatives that enhance operational velocity. Experience in context and spec engineering, systematically structuring data, constraints, and operational guidelines to optimize LLM performance. About The Job The Google Cloud Consulting Professional Services team guides customers through ...

cross-functional teams, driving technical deployments, and managing stakeholders. Preferred qualifications: Experience in systems design with the ability to explain model architectures, data analysis, feature engineering, and agent design patterns. Experience in business-aligned evaluation design to define metrics, collect data, and measure a program's effectiveness … impact. Experience in process reimagination, assessing legacy workflows, and designing automated, AI-driven alternatives that enhance operational velocity. Experience in context and spec engineering, systematically structuring data, constraints, and operational guidelines to optimize LLM performance. About the job The Google Cloud Consulting Professional Services team guides customers through ...

Computer Science, Artificial Intelligence, or a related field (or equivalent experience) Strong foundation in AI/ML concepts and practical experience with data analysis, feature engineering, and model development Experience working with large, complex datasets and applying statistical analysis Hands-on experience training, deploying, and maintaining machine learning ...

reproducible data products Own the data platform architecture, including ingestion frameworks, transformation patterns, orchestration strategies, and data governance standards Establish and enforce data engineering best practices covering schema evolution, data contracts, validation frameworks, and performance optimization Build scalable backend data services and APIs for analytics tools, product applications … architectural standards, conduct design reviews, and document patterns that support team scalability and maintainability Evaluate and recommend data technologies, tools, and platforms to improve engineering productivity and data platform capabilities Требования Degree in Computer Science, Mathematics, or a related field 5+ Years of experience as a Cloud Engineer, Data ...

will have experience/be familiar with the following: AI and LLMs Familiarity with LLM-powered apps and services, evaluation frameworks, prompt engineering, and other generative AI work — whether through professional experience, coursework, or personal projects. Curiosity about how LLM-based systems behave in production and how to evaluate … Solid grounding in statistics and probability — comfortable with hypothesis testing, distributions, and drawing defensible conclusions from data. Hands-on experience with exploratory data analysis, feature engineering, and building and evaluating ML models. Working knowledge of the core ML model lifecycle: data preparation, training, validation, and monitoring. Working style ...

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 ...

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 ...

scalable AI/ML platform supporting insurance use cases including pricing, claims automation, fraud detection, customer analytics and document intelligence. You will partner with engineering, data, security and risk stakeholders to enable reliable model development, deployment and monitoring in a regulated environment. Key Responsibilities Design and maintain platform capabilities … model training, feature engineering, deployment and observability across cloud and on-prem environments. Build CI/CD pipelines for ML (MLOps) including automated testing, packaging, model registry workflows and promotion across environments. Implement containerised deployments (Docker/Kubernetes) and orchestration for batch and real-time inference workloads. Establish ...

Design and develop predictive, machine learning, and Generative AI solutions. Build prototypes, proof-of-concepts, and production-ready analytical models. Perform data exploration, feature engineering, model development, and validation. Collaborate with data engineers and architects to operationalise solutions. Ensure solutions follow Responsible AI, governance, and security best practices. ...

Design and develop predictive, machine learning, and Generative AI solutions. Build prototypes, proof-of-concepts, and production-ready analytical models. Perform data exploration, feature engineering, model development, and validation. Collaborate with data engineers and architects to operationalise solutions. Ensure solutions follow Responsible AI, governance, and security best practices. ...

security, identity and compliance (Entra ID, RBAC, network isolation, data protection). Strong experience designing LLM‐based solutions, including Retrieval‐Augmented Generation (RAG), prompt engineering strategies and agent‐based architectures, leveraging frameworks such as Semantic Kernel, LangChain, and Microsoft Agent Framework. Deep practical experience with classical Machine Learning, including … supervised and unsupervised learning, feature engineering, model selection, training pipelines, evaluation frameworks and production lifecycle management, equivalent in depth to GenAI expertise. Proven ability to assess client use cases and make well‐reasoned architectural decisions between classical ML and Generative AI approaches; and articulate clearly why. Strong experience ...

improve the quality, relevance, and usefulness of content-focused products and services across Expedia Group. Working within the Product & Technology Machine Learning Science and Engineering organisation, you will translate research and experimentation into reliable, scalable production outcomes. The team works across content understanding, review intelligence, search relevance, ranking, recommendations … evaluate, and improve machine learning models and algorithms for Content AI applications. Design and implement end-to-end machine learning solutions, including data preparation, feature engineering, model training, validation, deployment, monitoring, and continuous optimisation. Apply statistical analysis, experimentation, and data-driven decision-making to assess model performance ...