51 to 75 of 697 MLOps Jobs in England

access management with OIDC/SAML and Azure Entra ID.* Experience with LLMs, RAG systems, prompt engineering and AI evaluation frameworks; familiarity with MLOps, model deployment and AI observability/guardrails; working use of AI-assisted development tools (e.g. Claude Code).* Familiarity with one or more of: trading ...

Azure, Databricks, and Snowflake.Extend and support a multi-cloud and hybrid cloud platform for Analytics workloads.Drive agile engineering practices, including CI/CD, DevSecOps, MLOps/LLMOps, automated testing, and engineering best practices.Collaborate with multi-functional teams to integrate AI agents, automation capabilities, and modern AI services into business workflows.Ensure ...

Flows).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.Education - BS in Computer Science, Engineering, Data Science, or equivalent technical fieldUnleash Your PotentialWhen ...

communication skills and experience working across engineering, data science, security, architecture, and product teams.Bonus pointsExperience with AI or machine learning platforms, model-serving infrastructure, MLOps, or data-intensive services.Knowledge of advanced networking, API management, distributed systems, service mesh, or zero-trust architecture.Experience with GitOps, policy as code, internal developer platforms ...

environments. Experience defining scalable AI architectures on cloud platforms such as Azure, AWS or GCP, leveraging cloud-native AI and data services. Understanding of MLOps and GenAIOps principles, including lifecycle management, monitoring, performance optimisation and operationalisation at scale. Exceptional stakeholder management, communication and leadership skills, with the ability to translate ...

Hands-on experience in developing and deploying AI solutions in a professional setting.Experience building data pipelines and working with structured and unstructured data.Experience with MLOps tools and best practices for model deployment, monitoring, and governance.Experience working in Agile delivery environments.Strong analytical and problem-solving skills, with attention to detail.Programming: Strong ...

e.g., AI coding assistants, automated testing generation) to enhance developer velocity and code quality across the portfolio.* Data Readiness: Architect robust, scalable data pipelines (MLOps/LLMOps) to support reliable model training, fine-tuning, and low-latency inference.**Technical Leadership & Governance*** Act as a senior technical leader and mentor ...

experience working across engineering, data science, security, architecture, and product teams.## Bonus points* Experience with AI or machine learning platforms, model-serving infrastructure, MLOps, or data-intensive services.* Knowledge of advanced networking, API management, distributed systems, service mesh, or zero-trust architecture.* Experience with GitOps, policy as code, internal developer ...

backend development — FastAPI, REST APIs, microservices architectureVector databases & embeddingsCloud platforms — Azure GCP, or AWS; deploying and managing AI/ML workloads at scaleVersion control & MLOps — Git, CI/CD pipelines, model versioning, monitoring in productionData handlingRequired — Experience & MindsetDemonstrated end-to-end delivery: problem build deployed solution iterationStrong experience with Generative ...

Advise clients on AI platform capability and implementation strategyTech environment: Python LLMs (prompt engineering, fine-tuning, RAG) LangChain/LangGraph Agent frameworks Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructureWhat you'll bring:- Experience designing enterprise AI or ML architectures- Strong grasp ...

clients on AI platform capability and implementation strategy Tech environment: Python LLMs (prompt engineering, fine-tuning, RAG) LangChain/LangGraph Agent frameworks Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructure What you'll bring: - Experience designing enterprise AI or ML architectures - Strong grasp ...

development (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, FastAPI, and AWS, Azure, GCP or Databricks. CI/CD, MLOps and LLMOps familiarity expected. Strong communication and stakeholder skills matter at every level. ...

tool use/function calling, RAG, agents, prompt engineering, or agentic patterns for enterprise workflows. Production ML/LLMOps: Experience with model deployment, monitoring, MLOps/LLMOps, and lifecycle management across cloud services (AWS Bedrock, Azure AI, GCP Vertex AI). AI Architecture & Security: Understanding of cloud reference architectures, identity ...

with AWS and/or GCP cloud platforms. Hands-on expertise in: Kubernetes Docker/Containers CI/CD pipelines Knowledge of: DevOps DevSecOps MLOps LLMOps Experience with Agentic AI frameworks and the Agentic Development Lifecycle (ADLC). Additional Eligibility Requirements Candidates must currently reside in the United Kingdom. Candidates ...

high-impact team managing enterprise-scale Azure solutionsWork on the intersection of data, AI, DevOps, and automationOpportunities to grow across data engineering, MLOps, and cloud automationA dynamic, learning-focused work environment with cutting-edge tools and processes ...

technical audiences and apply AI-enabled approaches to deliver practical business value.Bonus Points ForParticipation in Kaggle or other data science competitions.Experience with MLOps practices (CI/CD, model monitoring, DevOps integration).Familiarity with advanced NLP frameworks such as spaCy or Transformers and exposure to AI technologies including Generative ...

cybersecurity, or data platform certifications.Experience with platforms such as Azure, AWS, GCP, OpenAI, Anthropic, Mistral, Google/Gemini, Databricks, Snowflake, Kubernetes, vector databases, and MLOps/LLMOps tooling.Strong executive presence, technical storytelling, mentorship, stakeholder influence, and ability to simplify complex concepts for business and technical audiences.Ability to travel as required ...

engineering 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 may include ...

Generative AI. Demonstrated ability to architect end‐to‐end Data & AI solutions, with specific expertise in modern Generative AI concepts (e.g., fine‐tuning, RAG, MLOps for LLMs), using either open source and/or ISV tools such as Dataiku, Domino, DataRobot etc. Strong proficiency in a core programming language (e.g. ...

Generative AI.Demonstrated ability to architect end-to-end Data & AI solutions, with specific expertise in modern Generative AI concepts (e.g., fine-tuning, RAG, MLOps for LLMs), using either open source and/or ISV tools such as Dataiku, Domino, DataRobot etc.Strong proficiency in a core programming language (e.g., Python ...

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 ...

Learning Applied machine learning, computer vision, object detection, image classification, model development and evaluation, data annotation and curation, training pipelines, performance optimisation, edge ML, MLOps, deployment and maintenance of ML solutions, Python development, Python-based ML frameworks, PyTorch, TensorFlow, sklearn, OpenCV, NumPy, feature development, code review, pytest, linting, bug fixing ...

Familiarity with 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.What’s it like to work at Zego At Zego, we operate like a high-performing sports team. We come together as one, driven ...

orchestration, tool use/function calling, RAG, agents, prompt engineering, or agentic patterns for enterprise workflows.Production ML/LLMOps: Experience with model deployment, monitoring, MLOps/LLMOps, and lifecycle management across cloud services (AWS Bedrock, Azure AI, GCP Vertex AI).AI Architecture & Security: Understanding of cloud reference architectures, identity ...

maintain ML solutions on modern frameworks to meet functional business requirements, adhering to software engineering best practices and with exposure to version control, testing, MLOps, CI/CD and API designHands on experience in using one of 3 major cloud technologies (AWS, Azure or GCP) in a production environment ...