626 to 650 of 845 Distributed Systems Jobs in the UK excluding London

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

that transform business outcomes. Key Responsibilities AI/ML Strategy & Architecture: Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI), large language models (LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build … optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability ...

motivated Senior Software Engineer to join our Group Technology team in Milton Keynes. In this role, you will help develop, support and enhance business systems and applications using .NET technologies and SQL Server.We offer a hybrid working arrangement with one or two days per week in our Milton Keynes … including TDD Strong knowledge of object-oriented design and development skills Highly Desirable: Experience with concurrent programming techniques, parallelism, and threading Experience working with distributed systems and microservice architectures Experience with high-scalability projects involving cloud-based infrastructure design and implementation Microsoft certified status Connells Group ...

motivated Senior Software Engineer to join our Group Technology team in Milton Keynes. In this role, you will help develop, support and enhance business systems and applications using .NET technologies and SQL Server. We offer a hybrid working arrangement with one or two days per week in our Milton … including TDD Strong knowledge of object-oriented design and development skills Highly Desirable: Experience with concurrent programming techniques, parallelism, and threading Experience working with distributed systems and microservice architectures Experience with high-scalability projects involving cloud-based infrastructure design and implementation Microsoft certified status Connells Group ...