76 to 100 of 697 MLOps Jobs in England

generative AI services.Experience designing retrieval-augmented generation architectures using vector search, embeddings, enterprise data sources, access controls, and secure application integration patterns.Experience with MLOps, including model lifecycle management, CI/CD for ML, feature stores, model monitoring, experimentation, and deployment pipelines.Experience with AIOps, intelligent observability, automated remediation, anomaly detection ...

Python REST APIs Git CI/CD Containers Infrastructure as Code Testing AI systems Platform Engineering Kubernetes Azure AI Foundry Databricks Microsoft Fabric Snowflake MLOps/LLMOpstooling Consulting competencies TheAISolutionArchitect should be able to: Facilitate AI discovery workshops. Identify and prioritise business use cases. Estimate business value and ROI. Create ...

orchestration technologies.* Retrieval Augmented Generation (RAG) architectures.* API development and microservice design.* Cloud-native development (Azure preferred).* CI/CD automation and MLOps practices.* Vector databases and knowledge retrieval platforms.* Data modelling and distributed systems design.* AI observability, evaluation and governance frameworks.Desirable Experience* Experience within Financial Services or highly ...

Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions.* SQL and large-scale data analysis.* Cloud-based data science platforms and MLOps practices.* Data visualisation and storytelling tools.### Desirable Skills* Experience within financial services, regulated environments or market infrastructure.* Familiarity with Azure AI services and Microsoft ...

equivalent platforms.Developing high-quality, maintainable code and working with software engineering practices such as version control, testing, code review and CI/CD.Working with MLOps or workflow tools such as MLflow, Kubeflow, Argo or equivalent frameworks.Scaling models or analytical services for enterprise or operational use.Applying statistical methods, model evaluation techniques ...

equivalent platforms.Developing high-quality, maintainable code and working with software engineering practices such as version control, testing, code review and CI/CD.Working with MLOps or workflow tools such as MLflow, Kubeflow, Argo or equivalent frameworks.Scaling models or analytical services for enterprise or operational use.Applying statistical methods, model evaluation techniques ...

equivalent platforms.Developing high-quality, maintainable code and working with software engineering practices such as version control, testing, code review and CI/CD.Working with MLOps or workflow tools such as MLflow, Kubeflow, Argo or equivalent frameworks.Scaling models or analytical services for enterprise or operational use.Applying statistical methods, model evaluation techniques ...

concepts and applying them to business scenarios as neededDesirableExperience with/in:Microsoft Azure Data Scientist Associate (DP-100) certification or equivalent.Strong understanding of MLOps/DevOps concepts including model versioning, CI/CD, Automated retraining, lineage and governance.Experience with model risk management, Responsible AI and compliance controls in regulated ...

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

e.g. LangChain/LangGraph)• Python and modern data engineering• Snowflake and governed semantic layers• AWS/GCP cloud services• Vector databases• Data pipelines and MLOps tooling• Business intelligence and visualisation tools#LI-AB3What’s in it For You Hybrid Work Model: We’ve adopted a flexible hybrid working environment ...

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

business teams to deliver end-to-end solutions.**Tech environment**Python, LLMs (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes and GPU infrastructure.**What we're looking for**Proven enterprise AI or ML architecture design, strong cloud ...

deployments CI/CD experience with a focus on production ownership and reliability Understanding of data quality, testing and lineage best practices Desirable skills: MLOps or production machine learning experience Terraform, Ansible or other Infrastructure as Code tools PostgreSQL and modern data platforms Experience within Defence, National Security or regulated ...

/APIs LangChain/LangGraph Vector databases Embeddings and semantic search Hugging Face/open-source AI models Prompt engineering Model evaluation and optimisation MLOps/LLMOps Docker/Kubernetes CI/CD Cloud architecture AI security, governance and responsible AI About You You are likely to have previously worked ...

Build and maintain real-time AI pipelines using WebSockets and SSE, ensuring seamless low-latency delivery for voice (ASR/TTS) and text applications.Architecture & MLOps: Deploy and orchestrate models within containerized microservice architectures (Docker/Kubernetes), ensuring robust monitoring, security, and scalability.Collaborative Delivery: Work closely with Business Analysts and internal ...

domains. Ability to lead architectural discussions and technical trade‐offs without losing sight of the details. Familiarity with cloud infrastructure (AWS preferred) and modern MLOps practices. Commitment to people development: mentoring, performance conversations, and building high‐performing teams. Bonus: experience with NLP on financial contracts, RAG or LLM‐based applications ...

Science, Machine Learning, Operational Research, or Statistics. Academic, internship, or personal projects delivering data science outputs. Basic familiarity with CI/CD pipelines or MLOps concepts. Exposure to containerisation technologies (e.g., Docker). Some experience working with relational or NoSQL databases (e.g., PostgreSQL, MongoDB). Familiarity with Workday data structures ...

identity and access management with OIDC/SAML and Azure Entra IDExperience with LLMs, RAG systems, prompt engineering and AI evaluation frameworks; familiarity with MLOps, model deployment and AI observability/guardrailsStrong familiarity with AI-assisted development tools (e.g. Claude Code)Department overviewThe AI Hub is responsible for enabling ...

machine learning solutions from initial experimentation through to deployment. Strong knowledge of data science libraries such as Polars, Pandas, NumPy, Scikit-learn. Knowledge of MLOps tooling such as Weights & Biases, AirFlow, AWS SageMaker or Docker. Experience working with cloud platforms such as AWS, Azure or GCP. Experience working collaboratively ...

cost/latency optimisation).Exposure to MCP (Model Context Protocol) and tool-based/function-calling architectures.Experience deploying and operating machine learning models/MLOps pipelines (e.g. model serving, monitoring, retraining workflows).Experience with real-time/streaming systems.What’s in it for youOur rapidly growing, award-winning business offers ...

Computer Science, Data Science, Machine Learning, or related field.Proven experience building and deploying AI applications in large-scale production environments.Experience with MLOps practices and tools for managing the machine learning lifecycle.Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.Strong understanding of data preprocessing, feature engineering ...