25 of 25 MLOps Jobs in Edinburgh

.Experience building and deploying Generative AI solutions, including prompt engineering, fine-tuning, and evaluation of large language models (LLMs) or other generative architectures.Understanding of MLOps principles, including automated model training, CI/CD for ML, model versioning, monitoring, and retraining.Experience deploying AI and GenAI solutions on cloud platforms (AWS, Azure ...

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. ...

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 ...

habit of fixing the class of problem rather than the instance. AI and ML operations: Experience operating model serving, LLM inference or MLOps pipelines in production is a strong plus. Familiarity with model APIs, vector databases, MCP or orchestration frameworks helps. Networking and security: VPC design, service mesh and zero ...

DevOps and business teams to deliver end-to-end solutions.Tech environmentPython, 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 forProven enterprise AI or ML architecture design, strong cloud and modern data ...

controlStrong collaboration skills, working across engineering, security, data science and product teamsAnd it would be great if you had any of the following...Exposure to MLOps or SMLOps tooling and model lifecycle managementExperience supporting AI/ML pipelines, feature engineering or analytics platformsKnowledge of AI governance and secure adoption of generative ...

agreed requirements, delivery plans and quality standards.Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices.Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments.Apply responsible AI, security … equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps and production AI practices, including CI/CD, model versioning, monitoring, automated testing, retraining and performance optimisation. Experience using cloud platforms and cloud-native ...

third-party solutions to find opportunities for innovation and business value. Guide architectural decisions across AI platforms, model-serving infrastructure, data pipelines, and MLOps/LLMOps capabilities. Partner closely with Engineering teams to productionize AI solutions and drive operational excellence. Build, mentor, and lead high-performing teams of Data Scientists … native AI development using Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure AI Search, AWS AI Services, and modern cloud architectures. Experience implementing MLOps and LLMOps practices, including CI/CD, model lifecycle management, governance, and production operations at scale. COLLABORATION & COMMUNICATIONAbility to communicate complex technical concepts clearly ...

models, and third-party solutions to find opportunities for innovation and business value.Guide architectural decisions across AI platforms, model-serving infrastructure, data pipelines, and MLOps/LLMOps capabilities.Partner closely with Engineering teams to productionize AI solutions and drive operational excellence.Build, mentor, and lead high-performing teams of Data Scientists … cloud-native AI development using Azure AI Foundry, Azure Machine Learning, Azure OpenAI, Azure AI Search, AWS AI Services, and modern cloud architectures.Experience implementing MLOps and LLMOps practices, including CI/CD, model lifecycle management, governance, and production operations at scale.COLLABORATION & COMMUNICATIONAbility to communicate complex technical concepts clearly to technical ...

including machine learning models, data pipelines and application components that are secure, reliable and performant.Drive the operationalisation of AI solutions using modern engineering and MLOps practices, including CI/CD, model monitoring, testing and lifecycle management.Ensure solutions are developed in line with security, privacy, governance and responsible AI requirements, particularly … practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation approaches.Experience with MLOps and modern engineering practices, including CI/CD pipelines, model versioning, monitoring and automated testing.Experience deploying AI solutions on cloud platforms such as Azure ...

large language models and AI-assisted engineering. Excellent communication, facilitation and stakeholder-management skills. Desirable Platform engineering, Kubernetes or internal developer platforms. AI platforms, MLOps, prompt engineering or agentic workflows. AI governance and responsible AI adoption. Public-sector digital delivery or technology modernisation experience. Please apply today to be considered ...

into complex enterprise workflows.Bridge Design & Implementation: Oversee the full technical lifecycle, from selecting the right model architectures to ensuring robust CI/CD and MLOps pipelines.Inference & Infrastructure: Deploy and optimise models using cloud services like AWS Bedrock and Azure AI Foundry, or self-host them on GPU/CPU hardware … Evaluation: Implement frameworks and approaches to evaluate model performance against business objectives, both pre-deployment and on an ongoing basis as part of the MLOps lifecycle.Drive System Performance: Assess and optimise for performance, cost-efficiency, and reliability, ensuring AI outputs meet the rigorous standards required for our Security & Justice clients.System ...

organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building … Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data ...

workloads on AWS (or multi‐cloud with strong AWS depth).Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components).Proven ability to take research and prototype ...

organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building … Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data ...

integrations Fine‐tune, optimize, and deploy large language and multi‐modal models with a focus on scalability, reliability, and low‐latency performance Build scalable MLOps pipelines and cloud‐native AI applications to support secure, production‐grade deployments Collaborate with clients and cross‐functional teams to shape AI engineering strategy … enterprise or large‐scale production environments Strong software engineering expertise in Python, including backend development, API design, and distributed systems Solid understanding of scalable MLOps, observability, CI/CD practices, and cloud‐native AI deployment architectures Excellent communication, stakeholder management, and problem‐solving skills within agile delivery environments Bonus Points ...

technical leadership AWS, CI/CD, APIs, containers and modern programming languages Cloud-native engineering, automated testing, observability and infrastructure as code Developer platforms, MLOps, AI automation or agentic workflows Coaching agile teams and influencing technical and non-technical stakeholders The role offers hybrid working within the UK, with onsite ...

technical leadership * AWS, CI/CD, APIs, containers and modern programming languages * Cloud-native engineering, automated testing, observability and infrastructure as code * Developer platforms, MLOps, AI automation or agentic workflows * Coaching agile teams and influencing technical and non-technical stakeholders The role offers hybrid working within the UK, with onsite ...

full AI engineering lifecycle, from architecture to production deployment, working with multi-disciplinary teams across client projects. The role emphasizes scalable MLOps, low-latency AI, and hands-on development in a client-facing, agile environment within Capco’s Technology Delivery team. #J-18808-Ljbffr ...

Engineering: Deep prompt engineering & optimization skills for GenAI.Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI (RAG) for knowledge applications.GenAI ModelOps/MLOps & Governance: GenAI ModelOps/MLOps knowledge with ethical AI governance focus.Multimodal & Code Generation: Architected GenAI for multimodal (vision, audio, language) & code generation.ER&I GenAI Applications ...

role shapes AI strategy, leads teams and delivers scalable AI products and data-driven applications across complex environments, requiring collaboration with data scientists, MLOps/LLMOps engineers, business stakeholders and senior #J-18808-Ljbffr ...

supporting organisations as they move from strategy and experimentation through to enterprise deployment.You will work closely with AI Engineers, Data Scientists, Enterprise Architects, MLOps teams, business stakeholders and senior leadership to design, deliver and scale AI solutions that drive measurable business outcomes.Key responsibilities:·Translating business objectives into AI architecture strategies … prompt engineering, embeddings, semantic search and RAG patterns·Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies·Understanding of MLOps, LLMOps and model lifecycle management principles·Experience designing APIs and integrating AI solutions into enterprise environments·Strong understanding of modern data architectures and platform design ...

test and deploy machine learning models, analytical pipelines and data science components that are robust, scalable and maintainable.Support the operationalisation of ML solutions through MLOps practices, including model monitoring, versioning, automated testing, CI/CD and performance optimisation.Apply responsible AI, model explainability, security, privacy and governance considerations throughout the development … PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps and production ML practices, including CI/CD, model versioning, automated testing, retraining, monitoring and reproducible delivery.Experience using cloud platforms and data science environments such ...

supporting organisations as they move from strategy and experimentation through to enterprise deployment. You will work closely with AI Engineers, Data Scientists, Enterprise Architects, MLOps teams, business stakeholders and senior leadership to design, deliver and scale AI solutions that drive measurable business outcomes. Key responsibilities: Translating business objectives into … prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience designing APIs and integrating AI solutions into enterprise environments Strong understanding of modern data architectures and platform design ...

. You will bridge the gap between complex enterprise data strategies‐spanning Cloud Migrations, Data Mesh architectures, Real‐time Streaming, and Generative AI/MLOps pipelines‐and precise execution across globally distributed engineering pods of 100+ people. The Impact By pairing technical depth with executive gravitas, you will de‐risk … Fluency: Deep understanding of modern data stacks (Data Lakehouses, Data Mesh, Real‐time Streaming, ETL/ELT pipelines) and AI/ML lifecycle management (MLOps, GenAI integration, Model Governance). Ability to challenge architectural patterns and supervise technical teams without acting as the hands‐on architect. Cloud & Platform Mastery Expertise ...