26 to 50 of 67 MLOps Jobs in Scotland

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 ...

Models (LLMs), Retrieval Augmented Generation (RAG) and prompt engineering. - Experience building, training, testing and operationalising machine learning models across the full lifecycle. - Experience implementing MLOps practices, including model deployment, CI/CD pipelines and monitoring. - Strong understanding of data preparation, feature engineering, model evaluation and performance optimisation. - Experience working with ...

fits into a drug‐discovery or materials‐design workflow, plus familiarity with cheminformatics tooling (e.g. RDKit, OpenEye) — or willingness to pick these up. MLOps fluency: experiment tracking, data versioning, model serving, and observability of deployed models. A visible track record in the field — peer‐reviewed publications, open‐source contributions ...

cloud data warehousing principles. Expertise with cloud data warehouse solutions such as Databrick, Snowflake or Redshift. Proven experience in DataOps, CI/CD (MLOps is a plus) Exceptional written, verbal, and listening communication skills, with the ability to effectively explain complex technical concepts to both technical and non-technical audiences. ...

large language models and AI-assisted engineering tools, including their limitations, risks and operating considerations. Desirable experience includes AI platforms such as AWS SageMaker, MLOps and AI governance, platform engineering and developer portals, Kubernetes and related tooling, and work on public sector digital delivery or technology modernisation. Interested? Apply ...

e.g., Spark or similar) and scalable data processing environments. Exposure to cloud-based platforms (e.g., AWS, Azure, GCP or Databricks) and modern ML/MLOps practices. Proven track record managing and growing high-performing data science teams, including technical mentoring and delivery accountability. Strong stakeholder management skills, able to operate ...

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 ...

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 ...

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 ...

Head Resourcing Ltd is recruiting an experienced AI/Machine Learning Engineer Contractor in Glasgow on a hybrid basis. The initial contract is 3 months with the potential to extend, paying up to £500 per ...

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 ...

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 ...

agentic AI initiatives.Exposure to enterprise AI platforms such as Microsoft Copilot Studio, Power Platform, Power Automate, Azure AI, or similar ecosystems.Familiarity with SDLC, DevOps, MLOps, AI governance frameworks, or model lifecycle management.Experience leading or mentoring junior Business Analysts.Knowledge of project planning disciplines and broader programme delivery methodologies.Experience developing dashboards, reporting ...

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 ...

Agentic AI solutions. The ideal candidate brings a balanced mix of modern AI/ML delivery (LLMs/SLMs, RAG, tool-using agents, evaluation, MLOps) and backend/service engineering (Java and/or Python, APIs/microservices, testing, CI/CD, observability, reliability) on AWS and cloud-native platforms.This … automated evaluation to improve quality over time.Build and maintain data pipelines and processing workflows required for ML/GenAI use cases using cloud services.Apply MLOps practices across the lifecycle: experimentation, versioning, CI/CD, deployment, monitoring, and maintenance for models/prompts/agents.Implement robust testing (unit/integration), performance ...

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 ...

proof-of-concepts, pilots and production implementations.Collaborate with Agile delivery teams to embed AI capabilities into products and services.Establish CI/CD pipelines and MLOps practices.Drive technical quality, performance and operational resilience.Generative AI & Large Language ModelsDesign and implement solutions using Large Language Models (LLMs).Develop Retrieval-Augmented Generation (RAG) architectures.Implement … AI.Experience with Python and modern development frameworks.Strong understanding of APIs, microservices and cloud-native architecture.Experience with data platforms, databases and data engineering concepts.Knowledge of MLOps, DevOps and CI/CD practices.AI & DataHands-on experience with:Large Language Models (LLMs)Prompt engineeringRetrieval-Augmented Generation (RAG)Vector databasesAI orchestration frameworks such ...

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 ...

guide the strategy, architecture, and delivery of our next generation Hybrid AI Platform. In this role, you will provide leadership across AI infrastructure, MLOps, cloud native platform engineering, and operational excellence -setting direction for teams that build and run production grade AI/ML platforms on Kubernetes. You will drive … driven, cloud native platform automation using ArgoCD and Helm. Set standards for Linux systems management, platform hardening, and operational reliability across all AI infrastructure. MLOps & Model Lifecycle Management Define and evolve the enterprise MLOps architecture, enabling reproducible, automated, and governed AI model workflows. Lead teams in building and optimizing ...

software code development Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps Designs and implements data engineering solutions, leveraging modern big data technologies Contributes to software engineering communities of practice and events that explore new and emerging technologies Embraces … experience developing Production-scale Cloud-native data engineering solutions in commercial environments Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps stack Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds Preferred qualifications, capabilities, and skills Experience with data ...

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 ...