1 to 25 of 217 Permanent MLOps Jobs in the UK excluding London

/ML/LLM/GenAI solutions to meet business objectives. Manage, mentor, and guide a team of ML and MLOps engineers. Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency. Implement optimization strategies to fine-tune generative models for specific NLP use cases, ensuring high ...

related field, or equivalent practical experience Nice-to-Have Skills AWS Certified Machine Learning Engineer – Associate or an equivalent Azure certification Experience with MLOps, model evaluation and observability tooling Experience with Terraform and Kubernetes #J-18808-Ljbffr ...

pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs, generative AI, and prompt engineering. Knowledge of MLOps tools and frameworks (MLflow, Kubeflow, Airflow). Familiarity with SQL, NoSQL, and distributed data technologies. Experience deploying AI models in production environments. Publications, patents, or open-source contributions ...

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 ...

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 ...

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 ...

experience and a track record of building deployment and release automation Experience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps) Practical experience with observability tooling (metrics, logging, tracing) and production incident response Experience operating ML/LLM workloads in production (LLMOps, inference reliability, cost/ ...

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 ...

Relevant cloud, AI, or security certifications. Experience deploying ML models into production environments. Experience with Kubernetes, OpenShift, or cloud-native deployment architectures. Experience with MLOps tooling (e.g. MLflow, Kubeflow, model monitoring platforms). Experience applying DevSecOps practices within cloud or controlled environments. Exposure to large language models or generative ...

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 ...

Science, Engineering, or a related technical field (or equivalent applied experience) Preferred qualifications, capabilities, and skills Experience operating ML/LLM workloads in production (MLOps, inference reliability, cost/performance management) Experience within financial services technology Familiarity with JPM-internal platform, cloud, and observability tooling for internal candidates #J ...

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 ...

optimize relational data models using PostgreSQL. Deploy and manage backend services on cloud platforms, preferably Azure and/or GCP. Collaborate with DevOps/MLOps engineers on CI/CD pipelines, containerization, and deployment strategies. Monitor service health and performance, proactively addressing bottlenecks and reliability issues. Work within an Agile ...

foundation with proficiency in Python, cloud platforms (AWS/Azure), APIs, and full-stack development to rapidly prototype and productionise AI applications. Experience with MLOps practices including model deployment, monitoring, evaluation, and CI/CD pipelines with delivering AI solutions from concept to production. Some other highly valued skills ...

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 ...

native data services and event-driven architectures Experience building data products that support analytics, reporting, machine learning, or AI use cases Knowledge of MLOps, AI Engineering, Agentic AI, or Generative AI implementation patterns Experience leading distributed engineering teams Experience establishing engineering standards, reusable frameworks, and community-of-practice initiatives Knowledge ...

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 ...

Skills: Hands-on experience with data lineage tools and techniques, including graph & vector databases and metadata management platforms Hands-on experience with LLM Ops, MLOps, and AI/ML platform deployment at scale Familiarity with business-led analytics delivery models and rapid prototyping frameworks Experience with AI/ML governance ...

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 ...

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/ ...

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 ...

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 ...