1,126 to 1,150 of 2,166 Machine Learning Jobs in London

. Ability to design and implement high-performance, scalable backend solutions. Solid understanding of web security best practices. Preferred Skills: Familiarity with AI or machine learning concepts, particularly in integrating AI into professional workspaces. Experience working with real-time systems , messaging queues, and event-driven architectures. Knowledge of More ❯

collaborate closely with analytics, engineering, and data science teams to drive insights and innovation. Key Responsibilities Build and maintain data models that support analytics, machine learning, and reporting needs. Design, implement, and optimize scalable ELT processes using modern data stack technologies. Ensure data accuracy and reliability across multiple More ❯

. Ability to design and implement high-performance, scalable backend solutions. Solid understanding of web security best practices. Preferred Skills: Familiarity with AI or machine learning concepts, particularly in integrating AI into professional workspaces. Experience working with real-time systems , messaging queues, and event-driven architectures. Knowledge of More ❯

collaborate closely with analytics, engineering, and data science teams to drive insights and innovation. Key Responsibilities Build and maintain data models that support analytics, machine learning, and reporting needs. Design, implement, and optimize scalable ELT processes using modern data stack technologies. Ensure data accuracy and reliability across multiple More ❯

s working to help connect people around the globe. You will have a keen interest in relevant engineering fields, including (but not limited to) machine learning and artificial intelligence, distributed software systems, storage systems, data warehousing and analytics, database systems, operating systems, networking systems, programming languages, compilers & runtime More ❯

functional teams to integrate AI-powered solutions into the Explore platform, optimise models for better content discovery, and support the deployment and maintenance of machine learning models in production. Staying updated on AI advancements; you'll continuously experiment with new methodologies to enhance the user experience. Key skills More ❯

with AWS technologies Experience in scripting for automation (e.g. Python) and advanced SQL skills. Experience with theory and practice of information retrieval, data science, machine learning and data mining Experience working directly with business stakeholders to translate between data and business needs Experience with data visualization using Tableau More ❯

functional teams to integrate AI-powered solutions into the Explore platform, optimise models for better content discovery, and support the deployment and maintenance of machine learning models in production. Staying updated on AI advancements; you'll continuously experiment with new methodologies to enhance the user experience. Key skills More ❯

spread analysis, fuel cost adjustment forecast, maintenance program adjusted system availability, sensitivity and price visualisation tools. Explore innovative ideas using advanced statistical analysis and machine learning techniques to improve forecast inputs and support long-term trading strategies. Provide analytical support to the team in the UK. Minimum Requirements More ❯

functional teams to integrate AI-powered solutions into the Explore platform, optimise models for better content discovery, and support the deployment and maintenance of machine learning models in production. Staying updated on AI advancements; you'll continuously experiment with new methodologies to enhance the user experience. Key skills More ❯

Life Cycle. Advanced knowledge of agile methodologies such as CI/CD, application resiliency, and security. Proficiency in specific technical disciplines like cloud, AI, machine learning, or mobile. Deep understanding of the financial services industry and IT systems. Experience with cloud-native technologies. Preferred qualifications, capabilities, and skills More ❯

Fluent in English with strong communication and collaboration skills. Preferred Qualifications Experience with big data processing frameworks like Apache Flink or Spark. Familiarity with machine learning models and AI-driven analytics. Understanding of front-end and mobile app interactions with backend services. Expertise in cloud-native application development More ❯

with AWS technologies - Experience in scripting for automation (e.g. Python) and advanced SQL skills. - Experience with theory and practice of information retrieval, data science, machine learning and data mining - Experience working directly with business stakeholders to translate between data and business needs - Experience with data visualization using Tableau More ❯

to oversee the platform's ongoing operation and development and grow its adoption throughout AXA XL. The platform facilitates the entire lifecycle of data, machine learning, and AI, including scalable data transformation, engineering, deployment, and operations. It now integrates Azure AI for advanced document handling and provides shared More ❯

as CI/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) In-depth knowledge of the financial services industry and their IT systems Practical cloud native experience AWS Atlas Exposure to More ❯

to launch. This involves working across the entire stack — from front-end (written in React/TypeScript), back-end (written in Kotlin and Python), machine learning (agentic workflows, entity matching), to infrastructure (AWS, Docker). Working at a startup so early, it's common to kick off a More ❯

using storytelling techniques to effectively communicate insights and recommendations. Stay up to date with the latest advancements, trends, and research in AI, data science, machine learning, and related technologies. Document experimental methodologies, findings, and insights to ensure transparency, reproducibility, and knowledge sharing within the team and across the More ❯

to launch. This involves working across the entire stack — from front-end (written in React/TypeScript), back-end (written in Kotlin and Python), machine learning (agentic workflows, entity matching), to infrastructure (AWS, Docker). Working at a startup so early, it's common to kick off a More ❯

such as an MBA or a Master's in Cyber Security, or equivalent experience. Professional certifications like CISSP, CISM, or CEH. Experience with UEBA, machine learning and AI in threat detection. Familiarity with global financial systems and regulations. A track record of successful project management in a cyber More ❯

services. 2. Fraud Detection and Prevention Real-Time Monitoring: Implement AI algorithms to detect and flag unusual transactions in real-time. Predictive Analytics: Use machine learning models to predict potential fraud based on historical data and behavioural patterns. 3. Loan Processing Automation Credit Scoring: AI can evaluate creditworthiness More ❯

for our global customers. Whether it is a strategic conversation that needs to be had with customers or a technical discussion with architects and machine learning engineers, we have a wide variety of roles in the team that gives our employees the ability to expand their skills and More ❯

Experience using Cloud Storage and Computing technologies such as AWS Redshift, S3, Hadoop, etc. - Experience with theory and practice of information retrieval, data science, machine learning and data mining. - Experience with theory and practice of design of experiments and statistical analysis of results. - Experience with Python, Spark SQL More ❯

Experience using Cloud Storage and Computing technologies such as AWS Redshift, S3, Hadoop, etc. Experience with theory and practice of information retrieval, data science, machine learning and data mining. Experience with theory and practice of design of experiments and statistical analysis of results. Experience with Python, Spark SQL More ❯

building internal data communities or enablement programs Working with diverse data sources (APIs, CRMs, SFTP, databases) and formats (Parquet, JSON, XML, CSV) Exposure to machine learning models or AI agents Why Join Us Help shape the future of data in an organization that treats data as a product More ❯

Python experience for programming Databases, SQL and NoSQL (CosmosDB, KQL) Data Modelling: Kimball frameworks and 3NF Nice To Have Databricks Power BI AI/ML Azure Infrastructure DevOps Certifications Microsfot certified: fabric Analytics Engineer Associate DP-203 Azure data Engineering AZ-305 Azure Solutions Architect. If this sounds like you More ❯