51 to 75 of 537 MLOps Jobs in London

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

/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 ...

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 ...

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 ...

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 ...

across financial services, healthcare, manufacturing, retail, public sector, or other enterprise industries. Cloud & Infrastructure: Hands‐on experience with cloud architecture, Infrastructure‐as‐Code, DevOps, MLOps, or enterprise platform engineering. Pre‐sales & Customer Success: Experience supporting enterprise sales cycles, solution demonstrations, technical workshops, or proof‐of‐concept engagements. Enterprise Integrations: Experience ...

Engineering (Specialist Team)The impact you will have:Lead the architectural design of production-grade ML workloads on our unified platform, encompassing the entire MLOps lifecycle from end-to-end pipeline creation and optimization (training/inference) to seamless integration with cloud-native services.Provide advanced technical support to the Solution ...