76 to 100 of 271 MLOps Jobs in the UK excluding London

Cluster management Unity Catalog Preferred Skills Databricks Certified DataEngineer Professional/Databricks Certified Architect. Experience with: MLflow Databricks Machine Learning Feature Store Model deployment MLOps Knowledge of streamingtechnologies: Structured Streaming Kafka Experience with datagovernance, compliance,and enterprise securityframeworks. Key Competencies Strong Databricks architectureand implementation expertise. Ability to designscalableand cost-efficientLakehouse ...

Skills:Professional certifications in AWS, Azure, GCP, or Data Engineering.Experience within aerospace, defence, manufacturing, or highly regulated industries.Knowledge of AI/ML platforms and MLOps practices.Experience with graph databases and knowledge engineering solutions.Experience implementing data mesh or data fabric architectures.Enterprise Architecture experience.Experience leading large-scale data modernisation programmes.Knowledge of defence ...

technologies, collaboration platforms, and SQL-based databases. Strong experience working within AWS environments and services. Desirable Experience AI governance and responsible AI frameworks. MLOps and LLMOps tools and methodologies. Prompt engineering and model fine-tuning. Agentic AI frameworks such as LangGraph, AutoGen, or CrewAI. AI orchestration platforms such ...

certifications in AWS, Azure, GCP, or Data Engineering. Experience within aerospace, defence, manufacturing, or highly regulated industries. Knowledge of AI/ML platforms and MLOps practices. Experience with graph databases and knowledge engineering solutions. Experience implementing data mesh or data fabric architectures. Enterprise Architecture experience. Experience leading large-scale data ...

knowledge of knowledge graphs and semantic data modelling, using technologies such as RDF, LPG, Neo4j, and SpannerGraph. Strong understanding of modern cloud platforms and MLOps tooling, including GCP and containerisation with Docker. Excellent problem-solving skills, with the ability to translate research concepts into scalable, production-ready systems. Desirable: Experience ...

knowledge in the following: Python AWS Kubernetes Spark & distributed computing dbt Terraform Data Warehousing (we use Databricks but experience with other platforms is fine) MLOps implementation (desirable but not required) Airflow (or other orchestration tooling) Governance Why else you'll love it here Wondering what the salary for this role ...

data‐driven systems in production or near‐production settings. Experience with generative AI systems, LLM‐enabled applications or evaluation pipelines. Experience with cloud platforms, MLOps tooling, model serving or platform engineering. Advanced use of Linux, Docker, version control, CI/CD and service‐oriented deployment practices. Experience working across ...

working with AWS-native data services and event-driven architecturesExperience building data products that support analytics, reporting, machine learning, or AI use casesKnowledge of MLOps, AI Engineering, Agentic AI, or Generative AI implementation patternsExperience leading distributed engineering teamsExperience establishing engineering standards, reusable frameworks, and community-of-practice initiativesKnowledge of data ...

decoding)Proven track record of developing and deploying models at scaleExpertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platformsStrong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes) With preferred backgrounds covering some of the following:Experience with speech-to-text or text ...

track record of developing and deploying models at scale Expertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms Strong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes) With preferred backgrounds covering some of the following: Experience with speech-to-text or text ...

agreed requirements, delivery plans and quality standards.Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices.Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments.Apply responsible AI, security … equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps and production AI practices, including CI/CD, model versioning, monitoring, automated testing, retraining and performance optimisation. Experience using cloud platforms and cloud-native ...

agreed requirements, delivery plans and quality standards.Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices.Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments.Apply responsible AI, security … equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps and production AI practices, including CI/CD, model versioning, monitoring, automated testing, retraining and performance optimisation. Experience using cloud platforms and cloud-native ...

agreed requirements, delivery plans and quality standards.Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices.Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments.Apply responsible AI, security … equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps and production AI practices, including CI/CD, model versioning, monitoring, automated testing, retraining and performance optimisation. Experience using cloud platforms and cloud-native ...

agreed requirements, delivery plans and quality standards.Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices.Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments.Apply responsible AI, security … equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps and production AI practices, including CI/CD, model versioning, monitoring, automated testing, retraining and performance optimisation. Experience using cloud platforms and cloud-native ...

agreed requirements, delivery plans and quality standards.Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices.Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments.Apply responsible AI, security … equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps and production AI practices, including CI/CD, model versioning, monitoring, automated testing, retraining and performance optimisation. Experience using cloud platforms and cloud-native ...

third-party solutions to find opportunities for innovation and business value. Guide architectural decisions across AI platforms, model-serving infrastructure, data pipelines, and MLOps/LLMOps capabilities. Partner closely with Engineering teams to productionize AI solutions and drive operational excellence. Build, mentor, and lead high-performing teams of Data Scientists … native AI development using Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure AI Search, AWS AI Services, and modern cloud architectures. Experience implementing MLOps and LLMOps practices, including CI/CD, model lifecycle management, governance, and production operations at scale. COLLABORATION & COMMUNICATIONAbility to communicate complex technical concepts clearly ...

models, and third-party solutions to find opportunities for innovation and business value.Guide architectural decisions across AI platforms, model-serving infrastructure, data pipelines, and MLOps/LLMOps capabilities.Partner closely with Engineering teams to productionize AI solutions and drive operational excellence.Build, mentor, and lead high-performing teams of Data Scientists … cloud-native AI development using Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure AI Search, AWS AI Services, and modern cloud architectures.Experience implementing MLOps and LLMOps practices, including CI/CD, model lifecycle management, governance, and production operations at scale.COLLABORATION & COMMUNICATIONAbility to communicate complex technical concepts clearly to technical ...

environments. You will play a key role in designing, building, and maintaining scalable, secure, and high-performing infrastructure, while working closely with Data Engineers, MLOps Engineers, and Solution Architects. Key Responsibilities Design, build, and maintain CI/CD pipelines using GitLab CI for reliable, automated deployments to Azure Kubernetes Service ...

Models (LLMs), Retrieval Augmented Generation (RAG) and prompt engineering. - Experience building, training, testing and operationalising machine learning models across the full lifecycle. - Experience implementing MLOps practices, including model deployment, CI/CD pipelines and monitoring. - Strong understanding of data preparation, feature engineering, model evaluation and performance optimisation. - Experience working with ...

Teams. Strong communication skills and the ability to work with both technical and non-technical stakeholders. Desirable Experience AI governance and responsible AI practices. MLOps or LLMOps environments. Agentic AI frameworks such as LangGraph, CrewAI or AutoGen. AI orchestration tools such as N8N. Data governance and Microsoft Purview. Prompt engineering ...

practices, including testing, version control and code reviews. Exposure to cloud platforms, containerisation and modern deployment practices. Knowledge of CI/CD, DevOps or MLOps principles would be highly beneficial. Excellent communication skills and the ability to engage effectively with both technical and business stakeholders. Degree in a quantitative discipline ...

needed to put machine learning into production at scale. You'll have a meaningful say in how the deployment framework, model registry and wider MLOps capability are built. You won't simply inherit someone else's setup. If you've reached the point where you want to build the systems ...

needed to put machine learning into production at scale. You'll have a meaningful say in how the deployment framework, model registry and wider MLOps capability are built-not simply inherit someone else's setup. If you've reached the point where you want to build the systems behind production ...

advanced AI, and specifically: The management of people, process, documentation associated with the development, deployment, maintenance, training and operational management of Machine Learning solutions (MLOps) The management of people, process, documentation, maintenance and operational management of Generative AI solutions (GenAIOps/LLMOps) Manage, objectively assess and track Technology Readiness Levels ...

fits into a drug‐discovery or materials‐design workflow, plus familiarity with cheminformatics tooling (e.g. RDKit, OpenEye) — or willingness to pick these up. MLOps fluency: experiment tracking, data versioning, model serving, and observability of deployed models. A visible track record in the field — peer‐reviewed publications, open‐source contributions ...