18 of 18 Permanent MLOps Jobs in Central London

solutions on GCP leveraging Vertex AI, BigQuery, Cloud Run, secure API integrations; build scalable, resilient, compliant architectures; integrate AI services into existing applications. Data, MLOps & Engineering: Work with Data Engineers and Analysts to prepare, embed, and manage data (vector databases, embeddings); implement CI/CD, monitoring, logging, model performance tracking ...

models into Azure enterprise environments. Azure Databricks, Azure Machine Learning and ideally Azure AI Foundry. Building production AI applications using LangChain, LangGraph and Python. MLOps/LLMOps including deployment, monitoring, governance and lifecycle management. RAG, vector databases, prompt engineering and tool-calling patterns. Building end-to-end AI/ ...

expertise preferred, with hands‐on exposure to AWS and GCP. Experience integrating AI into distributed systems, microservices, APIs, and event‐driven architectures. DevOps and MLOps experience including CI/CD, IaC, automated testing, observability, and deployment automation. Familiarity with data engineering, ML models, Responsible AI, and enterprise governance. Ability ...

concepts. Excellent programming skills in Python. Demonstrated experience in building, validating, deploying, monitoring, and updating production ML and AI models. Hands-on experience with MLOps and AIOps infrastructure and tooling. Proficient in problem-solving and analytical reasoning. Exceptional communication and collaboration skills. Experience with ML frameworks such as TensorFlow, PyTorch ...

software development concepts like CI/CD, Version Control, Containers (Docker & Kubernetes) and proven track record of deploying ML models to production and established MLOps concepts. A good command of analytical programming and visualisation languages and libraries (SQL, python, matplotlib, etc.) as well as some of the supporting tools ...

associated architecture patterns Experience designing and managing APIs including REST and GraphQL Strong understanding of microservices and serverless architectures Practical experience with DevOps and MLOps practices including CI/CD pipelines Knowledge of security frameworks, identity management and authentication standards Desirable Skills for the AI Solutions Architect: Experience with enterprise ...

into enterprise platforms Collaborating closely with business stakeholders to translate requirements into scalable AI solutions Driving best practice across AI governance, model monitoring and MLOps Evaluating emerging AI technologies and identifying opportunities for innovation Skills & Experience We're looking for candidates with experience across several of the following: Commercial experience … learn Experience with Generative AI technologies including LLMs, LangChain or LlamaIndex Hands-on experience building RAG solutions and working with vector databases Experience with MLOps, CI/CD and containerisation Strong SQL skills and experience working with large datasets Cloud experience across Azure, AWS or GCP Excellent communication skills with ...

Mathematics Computer Science or a related quantitative discipline Desirable Skills for the Data Scientist: Experience with deep learning frameworks advanced modelling techniques Familiarity with MLOps concepts model monitoring deployment pipelines Exposure to tools such as Databricks MLflow feature stores Experience working in Agile product-led delivery environments Understanding of data ...

learning frameworks, and Generative AI/LLM components. Pipelines: Develop and optimize Retrieval-Augmented Generation (RAG) pipelines, vector databases, and scalable data processing streams. MLOps: Implement model deployment, monitoring, testing, and lifecycle management using standard CI/CD and containerized workflows. Architecture: Contribute to technical design decisions, trade-off analyses … Azure, or GCP) using Docker and Kubernetes. Engineering: Strong software engineering fundamentals, including version control, testing, and API/microservices architecture. Experience with MLOps platforms (e.g., MLflow, SageMaker) or agentic AI frameworks. Familiarity with secure development practices or regulated/high-compliance environments. Background in NLP, computer vision, or data ...

engineering excellence across the team. Partner with sales and tech leadership to define requirements for high‐value opportunities, deploying specialized experts (Machine Learning Operations (MLOps), Generative Media (GenMedia), or Agentic systems) to key accounts. Lead technical hiring for FDE, evaluating AI/ML expertise, systems engineering, and coding skills ...

hybrid in London, moving AI from prototype to production across cloud-native platforms. Responsibilities include AI solution design, cloud engineering on GCP, data, MLOps, Responsible AI governance, and collaboration with underwriters and operations. Strong Python and LLM experience required. #J-18808-Ljbffr ...

enterprise-scale operating models and shared services environments is beneficial. Required Skills AI & Agent Platforms: Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry Data & MLOps: Databricks, Azure SQL, ADLS, Azure AI Search Cloud & Integration: Microsoft Azure, API Management, Containers Identity & Security: Azure Entra ID, Key Vault, RBAC Observability & Governance: Logging ...

solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance and best practices * Translating business requirements into cloud-native AI and data architectures across Azure, AWS and GCP * Collaborating with technical and non-technical … stakeholders to deliver measurable business value * Supporting innovation initiatives, reusable assets, thought leadership and client proposals Candidates should have strong experience in AI Engineering, MLOps and cloud-native AI platforms, alongside hands-on knowledge of technologies such as LangChain, LlamaIndex, MLflow, Kubernetes, Docker and CI/CD tooling. Applicants will ...

production environment — not just notebooks. You've owned models after they ship and know how to keep them healthy. Full‐Lifecycle Delivery (MLOps): Comfortable delivering the end‐to‐end production lifecycle — model training, versioning, monitoring, and champion/challenger experimentation — without relying on a dedicated ML engineering team to carry … what to do about it. [Bonus] Experience with VertexAI TOOLS & TECHNOLOGIES Languages: Python, SQL Data & Transformation: dbt, Snowflake, BigQuery Visualisation & BI: Looker Engineering & MLOps: Docker, GitHub Workflow & Orchestration: Vertex AI Pipelines (GCP), Kubeflow LLMs & GenAI: Gemini API, Claude API INTERVIEW PROCESS Step 1: People Team Screening Call (30 min) Step ...

Intelligence Architect: Proven experience architecting solutions across Generative AI, Agentic AI, machine learning and automation Strong understanding of prompt engineering, RAG pipelines, model tuning, MLOps and LLMOps Experience delivering enterprise‐scale RAG solutions using LLMs and vector databases Ability to design AI platforms that integrate with existing enterprise technology stacks … services Solid software engineering foundation for building scalable, maintainable AI systems Advanced Python expertise with AI and ML frameworks Experience with MLOps and LLMOps tooling including containerisation and orchestration platforms Proven experience delivering applications using state‐of‐the‐art LLMs including prompt design, fine‐tuning and evaluation Strong understanding ...

experimentation with A/B and Multi-armed bandit testing frameworks, power analysis, variance reduction, and online-offline alignment. Work together with Data Engineering, MLOps, and Game Tech teams to guarantee dependable data foundations, feature accessibility, and model deployment pathways. Build internal data products to improve the speed and quality … problem definition to production deployment and monitoring. Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics. Hands-on experience in software engineering, MLOps, and deploying machine learning models at scale. Proficiency in SQL, Python, and familiarity with big data technologies (e.g., Kafka, Spark) and/or cloud platforms ...

MLOps Engineer (Platform/DevOps) - AI Platform - FULL TIME ONSITE We're partnering with a leading organisation on a high-profile AI initiative, seeking an experienced MLOps/Platform Engineer to build and scale infrastructure supporting advanced AI solutions. The Role You'll play a key role in designing ...

will design, develop, and deploy AI solutions across secure environments, building end-to-end ML pipelines, RAG components, and scalable data processing. Responsibilities include MLOps, architecture decisions, and collaborating with cross-functional teams to deliver production-ready AI systems with strong emphasis on security and compliance. #J-18808-Ljbffr ...