76 to 100 of 702 MLOps Jobs in the UK

technical and business stakeholders. Desirable Experience with Unity Catalog or similar data governance frameworks. Experience with Terraform or Databricks Asset Bundles. Exposure to MLflow, MLOps or AI and Generative AI workloads. Experience with streaming technologies such as Kafka or Structured Streaming. Databricks certification. Previous consulting or client-facing delivery experience. ...

Azure and Databricks, and familiarity with Azure DevOps tools like Boards, Repos, and Pipelines. Good knowledge of explainable AI and best practices in MLOps and LLMOps, with the ability to explain their importance. Strong programming skills in Python and SQL, with the ability to present data insights clearly to different ...

Azure and Databricks, and familiarity with Azure DevOps tools like Boards, Repos, and Pipelines. Good knowledge of explainable AI and best practices in MLOps and LLMOps, with the ability to explain their importance. Strong programming skills in Python and SQL, with the ability to present data insights clearly to different ...

Azure and Databricks, and familiarity with Azure DevOps tools like Boards, Repos, and Pipelines. Good knowledge of explainable AI and best practices in MLOps and LLMOps, with the ability to explain their importance. Strong programming skills in Python and SQL, with the ability to present data insights clearly to different ...

inference. 4 Implement robust LLM evaluation frameworks to monitor output quality (hallucinations, relevance), manage token costs and ensure content safety/governance. 5 Utilise MLOps tools and Google’s Agent Development Kit (ADK) to design autonomous agents and optimise deployment workflows on Vertex AI. 6 Lead ...

threat-intelligence vocabularies. GenAI and GraphRAG : LLM-based extraction, retrieval orchestration, agent/tool integration, prompt design, evaluation, grounding, guardrails, explainability, and evidence traceability. MLOps and observability: Experiment tracking, model versioning, deployment, monitoring, drift and quality checks, auditability, access controls, secrets management, and cost/performance management. Security Knowledge Graph ...

Azure and Databricks, and familiarity with Azure DevOps tools like Boards, Repos, and Pipelines. Good knowledge of explainable AI and best practices in MLOps and LLMOps, with the ability to explain their importance. Strong programming skills in Python and SQL, with the ability to present data insights clearly to different ...

threat-intelligence vocabularies. GenAI and GraphRAG : LLM-based extraction, retrieval orchestration, agent/tool integration, prompt design, evaluation, grounding, guardrails, explainability, and evidence traceability. MLOps and observability: Experiment tracking, model versioning, deployment, monitoring, drift and quality checks, auditability, access controls, secrets management, and cost/performance management. Security Knowledge Graph ...

infrastructure Transform innovative data science prototypes into robust, scalable, and secure production software, taking ownership of the 'path to production' Drive the adoption of MLOps best practices (CI/CD for ML, model versioning, feature stores) to accelerate the feedback loop for Data Scientists Effectively communicate the complexities ...

validation techniques to improve training pipelines Ensure data privacy and governance standards suitable for financial services Engineering best practices Contribute to DevOps and MLOps pipelines Implement robust version control, testing and CI/CD workflows Support reliable deployment and monitoring of models in production environments Technical leadership Mentor engineers ...

Multimodal Pipelines - Prior exposure to conversational voice pipelines or multimodal integrations via hyperscaler services. Advanced AI/ML Frameworks - Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms like Google Vertex AI or AWS Sagemaker. #J-18808-Ljbffr ...

Data Mesh or Lakehouse architectures. Familiarity with Kubernetes, Docker, and real-time streaming technologies (e.g. Kafka, Kinesis). Exposure to ML engineering pipelines or MLOps frameworks. The Zego ways of working Teams work better with time to collaborate and space to get things done. We call it Zego Hybrid: some ...

Data Mesh or Lakehouse architectures. Familiarity with Kubernetes, Docker, and real-time streaming technologies (e.g. Kafka, Kinesis). Exposure to ML engineering pipelines or MLOps frameworks. Pay Transparency At Zego, we are committed to pay transparency and equal pay practices. In compliance with EU pay transparency regulations, we proactively disclose ...

documenting and defending architectural decisions and engaging in thoughtful technical debate. Not required, but it’s a plus if you also have: Experience with MLOps/LLMOps frameworks and best practices A PhD in Computer Science, Electrical Engineering or a related field. A background or work experience in life‐sciences ...

scalable enterprise workloads, integrating with clients' incumbent technology estates. Implement hybrid‐cloud and multi‐cloud strategies using modern data infrastructure (Kafka, Spark, data lakes), MLOps practices, and deployment platforms. Ensure compliance with data privacy regulations (including UK GDPR) and responsible AI standards, incorporating governance, observability, and security controls into ...

experience with RAG architectures, Agentic AI frameworks, and orchestration tools such as LangChain, LangGraph, AutoGen, and CrewAI. Proven experience applying Agile delivery, DevOps, MLOps, and LLMOps practices to enterprise AI programmes. Strong cloud architecture experience across Azure, AWS, or GCP. Experience in model deployment, monitoring, observability, governance, versioning, and operational ...

data science solutions. Ensure sharing best practices and learnings with other squad members. Design and spearhead the development of Gen AI, AI Agents and MLOps platforms, applications, and solutions driven by GenAI, deep learning and machine learning to address business challenges and elevate product performance. Build standards and recommendations ...

data science solutions. Ensure sharing best practices and learnings with other squad members. Design and spearhead the development of Gen AI, AI Agents and MLOps platforms, applications, and solutions driven by GenAI, deep learning and machine learning to address business challenges and elevate product performance. Build standards and recommendations ...

data science solutions. Ensure sharing best practices and learnings with other squad members. Design and spearhead the development of Gen AI, AI Agents and MLOps platforms, applications, and solutions driven by GenAI, deep learning and machine learning to address business challenges and elevate product performance. Build standards and recommendations ...

Bridging Data & AI: A solid understanding of how AI fits into the broader data landscape, with an interest in integrating LLMs and AI/MLOps into client solutions. Collaborative Leadership: A proven track record of supporting multi-squad deliveries, guiding stakeholders through architectural trade-offs, and contributing to technical proposals. ...

machine learning, and generative AI technologies to deliver innovative business solutions. Continuously improve platform performance, scalability, and operational efficiency while supporting AI governance and MLOps best practices. Unfortunately we are unable to progress with candidates that require sponsorship at this time Skills we would love you to have Experience working ...

orchestration for AI workloads at scale (Docker, AKS).* Vector search at scale (Azure AI Search, Cosmos DB vector search).* LLMOps and MLOps tooling and automated evaluation harnesses.* Data privacy, security and compliance for AI systems, including responsible AI standards and GDPR considerations.* Delivery in regulated and high-governance ...

calling patterns.Containerisation and orchestration for AI workloads at scale (Docker, AKS).Vector search at scale (Azure AI Search, Cosmos DB vector search).LLMOps and MLOps tooling and automated evaluation harnesses.Data privacy, security and compliance for AI systems, including responsible AI standards and GDPR considerations.Delivery in regulated and high-governance environments.We ...

orchestration for AI workloads at scale (Docker, AKS).* Vector search at scale (Azure AI Search, Cosmos DB vector search).* LLMOps and MLOps tooling and automated evaluation harnesses.* Data privacy, security and compliance for AI systems, including responsible AI standards and GDPR considerations.* Delivery in regulated and high-governance ...

data pipelines and ML systems based on established patterns. Contribute to platform capabilities that support data transformation (DBT), pipeline orchestration (Airflow/Astronomer), MLOps workflows including model versioning and deployment automation and much more Support platform users including data engineers, ML engineers, data scientists, and analysts by troubleshooting issues, providing ...