1 to 25 of 71 MLOps Jobs in the North of England

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 ...

Experience of working with client sponsors, both technical and non-technical, to collaboratively design requirements and build out solutions.* Experience of designing and implementing MLOPs strategy and framework and proven track record in designing and delivering AI/ML solutions at scale, from concept to production.* Deep understanding of Generative ...

Intelligence, Data Science, or a related technology discipline Minimum 2:1 degree classification (or equivalent) Desirable Azure OpenAI, AWS Bedrock and Google Gemini experience MLOps, Data Engineering or Platform Engineering experience Experience leading technical teams Knowledge of Agentic AI, AI Agents and emerging AI frameworks What's On Offer? Opportunity ...

systems, or complex AI orchestration platforms that go beyond simple LLM integrations Advanced cloud‐native ML infrastructure – Deep expertise building sophisticated ML infrastructure, MLOps pipelines, model serving platforms, and cloud‐native AI systems at scale; experience optimizing cost and performance of production LLM deployments Financial services or analytical domain knowledge ...

systems, or complex AI orchestration platforms that go beyond simple LLM integrations Advanced cloud-native ML infrastructure – Deep expertise building sophisticated ML infrastructure, MLOps pipelines, model serving platforms, and cloud-native AI systems at scale; experience optimizing cost and performance of production LLM deployments Financial services or analytical domain knowledge ...

Computer Science, Machine Learning, or related field Nice to Have Published research in top ML venues (NeurIPS, ICML, ACL, CVPR). Experience with MLOps tools: MLflow, Weights & Biases, DVC. Familiarity with distributed training frameworks (DeepSpeed, Horovod). Experience with LLM fine-tuning and prompt engineering. Contributions to open-source ...

measurable outcomes. Nice to Have Experience with Bayesian modelling, optimisation algorithms or multi-armed bandits. Exposure to Generative AI, LLMs or agentic AI systems. MLOps experience, including CI/CD, model monitoring and deployment pipelines. Experience working within insurance, fintech, travel, ecommerce or other highly transactional environments. What ...

frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) - Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing) - LLMOps/MLOps - model versioning, deployment, monitoring, and rollback for AI services in production - Cloud-native engineering across major providers (AWS, Azure, or GCP), including their AI/ ...

Job Type: Permanent Build a brilliant future with Hiscox Company description Hiscox is a diversified international insurance group with a powerful brand, strong balance sheet and plenty of room to grow. Listed on the London ...

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 ...

workflow optimisation. Cloud and Deployment Knowledge – Familiarity with deploying AI models and AI‐enabled services using cloud platforms such as AWS, Azure, or GCP, MLOps practices, cloud architecture, containerisation, model monitoring, and secure production deployment patterns. Problem‐Solving and Communication skills – Ability to translate complex business and engineering challenges into ...

Prefect.* **Data Quality and Lineage** Familiarity with tools and techniques for data testing, documentation and lineage. Examples include Great Expectations or dbt.* **AI and MLOps** Understanding of how to operationalise machine learning models in production, including model packaging, monitoring and controlled deployment.* **Containerisation and Kubernetes** Confidence deploying applications in containerised ...

security capabilities, ensuring health, telemetry completeness, integration fidelity, detection coverage and continuous service improvement; partner across SOC, cloud, identity, data, application security, DevSecOps, MLOps, platform engineering and architecture; deliver executive-ready dashboards and reporting. Governance, Risk and Regulated-Environment Assurance: Translate policy, regulatory and framework expectations into testable requirements ...

Professional Services, or Advisory environments. Knowledge of FinOps, cloud cost optimisation, and total cost of ownership considerations. Relevant cloud and data certifications. Exposure to MLOps and AI platform engineering. Why Join? Define the organisation's data and AI strategy from the ground up. Work directly with senior leadership and influence ...

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 ...

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 ...

behaviours. Write production-quality Python and SQL, and work with engineers to integrate successful solutions into scalable AWS services, data pipelines, and APIs. Apply MLOps and LLMOps practices, including version control, automated tests, CI/CD, reproducible deployment, monitoring, drift detection, and rollback. Define and maintain offline and live evaluation ...

behaviours. Write production-quality Python and SQL, and work with engineers to integrate successful solutions into scalable AWS services, data pipelines, and APIs. Apply MLOps and LLMOps practices, including version control, automated tests, CI/CD, reproducible deployment, monitoring, drift detection, and rollback. Define and maintain offline and live evaluation ...

preparation, feature engineering, and feature stores, and understand why reproducibility and point-in-time correctness matter more than they first appear Have worked with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ...

preparation, feature engineering, and feature stores, and understand why reproducibility and point-in-time correctness matter more than they first appear Have worked with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ...

stakeholders, and scale successful solutions into production. Own the data platform strategy, ensuring well-governed data underpins AI and analytics initiatives. Establish robust MLOps and engineering practices covering deployment, monitoring, experimentation and governance. Champion practical AI adoption across Product and Engineering to improve ways of working. Build, lead and develop ...

security controls. Experience integrating AI solutions with Microsoft 365 technologies, collaboration platforms, and SQL-based databases. 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 ...

ability to work effectively across technical and business teams. Passion for innovation, continuous improvement and emerging data technologies. Desirable Experience with Scala. Exposure to MLOps, feature stores and machine learning platforms. Our Benefits Hybrid working - 2 days in the office and 3 days working from home 25 days annual leave ...

internal stakeholders.** *Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.** *Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.** *Experience of appropriate version control and environment management (such as venvs or Docker).** *Experience of writing technical project ...