601 to 625 of 845 Distributed Systems Jobs in the UK excluding London

STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L Role Overview: Turing is seeking a hands-on Machine Learning … combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines ...

STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L Role Overview: Turing is seeking a hands-on Machine Learning … combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines ...

STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L Role Overview: Turing is seeking a hands-on Machine Learning … combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines ...

STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L Role Overview: Turing is seeking a hands-on Machine Learning … combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines ...

STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L Role Overview: Turing is seeking a hands-on Machine Learning … combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines ...

STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L Role Overview: Turing is seeking a hands-on Machine Learning … combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines ...

STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L Role Overview: Turing is seeking a hands-on Machine Learning … combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines ...

STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L Role Overview: Turing is seeking a hands-on Machine Learning … combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines ...

mentor technical leaders across multiple greenfield projects. What we're looking for: Proven experience as a Solutions Architect or Principal Architect in complex systems Strong understanding of AI technologies Strong knowledge of cloud-native architectures (microservices, distributed systems) Expertise in secure-by-design principles and modern security ...

mentor technical leaders across multiple greenfield projects. What we're looking for: Proven experience as a Solutions Architect or Principal Architect in complex systems Strong understanding of AI technologies Strong knowledge of cloud-native architectures (microservices, distributed systems) Expertise in secure-by-design principles and modern security ...

mentor technical leaders across multiple greenfield projects. What we’re looking for: Proven experience as a Solutions Architect or Principal Architect in complex systems Strong understanding of AI technologies Strong knowledge of cloud-native architectures (microservices, distributed systems) Expertise in secure-by-design principles and modern security ...

Cambridge, Oxford. The role This is a greenfield platform engineering role with complete ownership over the core architecture. You'll design and build the systems powering real-time trading from the ground up, working directly with exceptional founders on one of the most ambitious infrastructure challenges … Architect the full platform stack (Python, TypeScript, Golang) handling trading engine, pricing models, hedging mechanisms and marketplace functionality. Build scalable, low-latency systems for real-time order matching, risk management and market data distribution. Design resilient infrastructure that can handle massive compute trading volumes with 24/7 reliability. ...

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 ...