1 to 25 of 209 Remote/Hybrid MLOps Jobs in England

following would be highly advantageous: Large Language Models (LLMs) Amazon Bedrock Azure AI Foundry PyTorch FastAPI Knowledge Graphs Kubernetes Docker Infrastructure as Code MLOps Event-Driven Architecture Vector Databases Retrieval-Augmented Generation (RAG) Technology Stack Python SQL FastAPI PyTorch Docker Kubernetes AWS Azure Git CI/CD Knowledge Graphs ...

Machine Learning Engineer, ML Engineer, Full Stack Engineer, Full Stack Developer, Python Developer, Senior Consultant Data Science, Data Scientist, Solutions Architect AI, LLM Engineer, MLOps Engineer, AI Software Engineer, Django Developer, FastAPI Developer, React Developer, Next.js Developer, TypeScript Developer, Azure OpenAI, Vertex AI, LangChain, LangGraph, CrewAI, Autogen, OpenAI Agents ...

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 ...

management, agent orchestration, guardrails, and responsible AI practices.* Experience integrating AI solutions with enterprise systems, data platforms, APIs, and cloud-native services.* Knowledge of MLOps, CI/CD, monitoring, model lifecycle management, and production support processes.* Familiarity with cloud security, governance, risk management, and compliance requirements for enterprise AI solutions. ...

LangGraph, CrewAI, AutoGen); mentoring specialists without formal authority; AI governance (security, privacy, observability) Desirable: cloud platforms (AWS/Azure/GCP); Docker/Kubernetes; MLOps/DataOps monitoring and testing Personal Attributes: transversal mindset, proactive problem-solver or systems thinker, continuous learner, adaptable and pragmatic Interested? Whether your strength ...

Intelligence, Data Science, or a related technology discipline Minimum 2:1 degree classification (or equivalent) Desirable Azure OpenAI, AWS Bedrock and Google Gemini experience MLOps, Data Engineering or Platform Engineering experience Experience leading technical teams Knowledge of Agentic AI, AI Agents and emerging AI frameworks What's On Offer? Opportunity ...

Intelligence, Data Science, or a related technology discipline Minimum 2:1 degree classification (or equivalent) Desirable Azure OpenAI, AWS Bedrock and Google Gemini experience MLOps, Data Engineering or Platform Engineering experience Experience leading technical teams Knowledge of Agentic AI, AI Agents and emerging AI frameworks What's On Offer? Opportunity ...

effectively within agile, cross-functional teams. Desirableskills andexperience: Experience building platforms or applications that support Data Science, Machine Learning, or AI workloads. Experience with MLOps tooling such as MLflow, Kubeflow, Vertex AI, or similar technologies. Knowledge of workflow orchestration platforms such as Apache Airflow. Experience with data processing technologies such ...

data with efficiency and ease. You will work closely with people from a wide variety of domains: Product Data Scientists, Analytics Engineers, ML Engineers, MLOps, MarTech and other Data Engineering teams. You will help manage our growing data needs and support increasingly complex business problems by building and promoting self ...

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 What’s in it For You? Hybrid Work Model: We’ve adopted a flexible hybrid working environment ...

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 ...

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 ...

databases (Microsoft SQL Server or equivalent) and NoSQL conceptsFamiliarity with microservices, API-first architecture and DevOps principlesNice to haveKnowledge of Azure AI Foundry, MLOps workflows and observability for AI modelsHands-on experience with Databricks for data processing in analytics-driven solutionsUnderstanding of RAG architectures, vector databases and advanced conversational ...

Factory and DatabricksOperationalize ML solutions, integrating feature stores, model registries and inference endpointsCollaborate with data scientists to deploy and monitor AI models using enterprise MLOps frameworksIntegrate GenAI-assisted development methods into data workflows for automation and efficiencyEnsure data governance, lineage, cataloging and quality frameworks across platformsOptimize platform performance, manage compute ...

evaluation engineering, and LLM guardrails/safety. Strong foundations in machine learning and deep learning, including distributed training, GPU workloads, and the full MLOps lifecycle (tracking, registry, serving, monitoring). Proficiency in Python and the ML ecosystem (PyTorch/Transformers, MLflow, Spark), and comfort building production-quality reference implementations. Experience ...

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/ ...

activities Partner with Data Engineers, Architects, Product Owners, and stakeholders throughout the delivery lifecycle Support the operationalisation of AI solutions through APIs, cloud platforms, MLOps, and downstream integration patterns Provide technical leadership and mentoring to junior practitioners Contribute to AI best practices, governance, responsible AI adoption, and continuous improvement initiatives … operationalising AI solutions in production environments Experience with vector databases, knowledge graphs, GraphRAG, entity resolution, recommendation systems, or semantic retrieval architectures Experience with MLOps, model monitoring, observability, and AI platform engineering Experience working within regulated or high-assurance environments, including Public Sector, Defence, Financial Services, or Critical National Infrastructure Experience ...

libraries (e.g., spaCy, NumPy, SciPy, Transformers). Understanding of big data and cloud technologies (Spark, Hadoop, Azure, AWS, or GCP). Deep expertise in MLOps principles, scalable model deployment, and model governance. Excellent communication and stakeholder management skills with the ability to translate data insights into business value. Bonus Points ...

system interactions Culture and Innovation Contribute to a culture of engineering excellence, collaboration, and continuous learning Stay curious about emerging tools and approaches in MLOps and applied AI, and bring ideas for improvement to the team Support responsible AI practices, contributing to explainability, auditability, and fairness in ML systems What ...

responsible AI principlesFamiliarity with cloud platforms including Azure AWS or GCP.Desirable (Not Mandatory):Experience implementing AI testing frameworks and governance controlsKnowledge of MLOps and model lifecycle managementUnderstanding of AI risk management and regulatory compliance frameworksCertifications in AI Cloud Quality Engineering or Test AutomationWe are a Disability Confident Employer:Capgemini ...

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 ...

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 ...

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 ...

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 ...

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 ...