326 to 350 of 357 Metadata Jobs in England

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

upload and ingest of large volumes of digitized and born digital content, configuring roles and security and integrating and mapping to catalogs and metadata standards Ideally with a background in either technical support or customer success within a records management or SaaS service environment, you will be familier with real … life best practice workflows, ingest routines and data/metadata mapping, using custom scripts and APIs. Equally you will have sound customer centric skills and a positve can-do attitude. Responsibilities: Lead portions of customer onboarding projects, including data ingest and metadata mapping. Develop and maintain scripts (Python, PowerShell ...

support for CMS and OSR ProjectWise systems. Set up new projects using BMS/ISO templates; ensure high standards for data and metadata integrity. Administer ProjectWise CONNECT Services (PW Web, Deliverables Mgmt, iTwin, Insights, Forms, etc.). Install, configure, and maintain ProjectWise Explorer, Rendition profiles, WRE workflows, attribute exchanges … administering Primavera P6 EPPM and/or ProjectWise in a technical capacity. Advanced understanding of project controls and document control principles (WBS, CPM, metadata configuration, workflows). Experience managing databases (Oracle, SQL Server), integrations (APIs, PowerShell), and middleware. Proficiency with ProjectWise infrastructure, environments, workflows, and Deliverables Management tools. Familiarity with ...

DevOps Engineer Location: Sheffield - Hybrid (3 days in office per week) Rate: Market rate (Inside IR35) Duration: 6 months The Role We are seeking a DevOps Engineer to own and evolve our Jenkins Shared Library ...

Engineer With AWS Migration experience. Job Description:- Lead the end-to-end SAS migration from Cloudera to AWS, ensuring seamless reconfiguration of SAS Metadata Server, Connectivity, and SAS jobs. Work directly with business stakeholders and engineering teams to plan, execute, and sign off migration activities. Key Responsibilities Lead SAS migration … activities from Cloudera (HDFS/Hive) to AWS. Oversee reconfiguration of SAS Servers, metadata, libraries, and connection points. Understand and redesign SAS jobs referencing HDFS/Hive to AWS equivalents. Manage prioritisation, planning, and progress tracking for 1000+ SAS jobs. Collaborate with business SMEs for coordinated testing and sign-offs. ...

Type: Permanent OR FTC Job Summary: Role Summary Lead the end to end SAS migration from Cloudera to AWS, ensuring seamless reconfiguration of SAS Metadata Server, Connectivity, and SAS jobs. Work directly with business stakeholders and engineering teams to plan, execute, and sign off migration activities. Key Responsibilities Lead … migration activities from Cloudera (HDFS/Hive) to AWS. Oversee reconfiguration of SAS servers, metadata, libraries, and connection points. Understand and redesign SAS jobs referencing HDFS/Hive to AWS equivalents. Manage prioritisation, planning, and progress tracking for 1000+ SAS jobs. Collaborate with business SMEs for coordinated testing and sign ...

other means) Occasionally, being able to lend hands-on support to the team working on and using the following technologies: Salesforce (APEX classes, metadata API, etc.) and Salesforce CLI (SFDX), Visual Studio Code, Git, CI/CD, AWS Qualifications People Leader: able to line manage others in line with … delivery of value efficiently and iteratively, and is responsible for fulfilling the teams commitments Technical knowledge and understanding of Salesforce (APEX classes, metadata API, etc.) and Salesforce CLI (SFDX); Sales cloud essential,?marketing cloud desirable, CPQ cloud?desirable,?Revenue cloud?desirable,?commerce cloud desirable,?data cloud?desirable,?Certina (FinancialForce) desirable ...

global, recognized brands, ensuring every product finds its buyer through intelligent content. What we do Wilgot provides the intelligence layer that transforms "thin" metadata into Intelligent Content optimized for the era of Agentic Commerce. Our Core AI Loop: Discover: Leverage AI and data analysis (customer queries, first-party data, Google … fine-tuning (you don't just call APIs). You know how to use AI to generate features that drive performance, moving beyond basic metadata into deep semantic understanding. Agentic Systems: Proven experience with agentic frameworks (e.g., LangGraph, PydanticAI) and managing memory and tool-calling in production. Engineering Mindset: Ability ...