20 of 20 Permanent MLOps Jobs in Lanarkshire

.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 ...

experience and a track record of building deployment and release automationExperience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps)Practical experience with observability tooling (metrics, logging, tracing) and production incident responseExperience operating ML/LLM workloads in production (LLMOps, inference reliability, cost/performance management ...

experience and a track record of building deployment and release automation Experience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps) Practical experience with observability tooling (metrics, logging, tracing) and production incident response Experience operating ML/LLM workloads in production (LLMOps, inference reliability, cost/ ...

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 skillsExperience with data ...

Computer Science, Engineering, or a related technical field (or equivalent applied experience)Preferred qualifications, capabilities, and skillsExperience operating ML/LLM workloads in production (MLOps, inference reliability, cost/performance management)Experience within financial services technologyFamiliarity with JPM-internal platform, cloud, and observability tooling for internal candidatesJ.P. Morgan ...

Science, Engineering, or a related technical field (or equivalent applied experience) Preferred qualifications, capabilities, and skills Experience operating ML/LLM workloads in production (MLOps, inference reliability, cost/performance management) Experience within financial services technology Familiarity with JPM-internal platform, cloud, and observability tooling for internal candidates ABOUT ...

engineering foundation with proficiency in Python, cloud platforms (AWS/Azure), APIs, and full-stack development to rapidly prototype and productionise AI applications.Experience with MLOps practices including model deployment, monitoring, evaluation, and CI/CD pipelines with delivering AI solutions from concept to production.Some other highly valued skills may include ...

Skills:Hands-on experience with data lineage tools and techniques, including graph & vector databases and metadata management platformsHands-on experience with LLM Ops, MLOps, and AI/ML platform deployment at scaleFamiliarity with business-led analytics delivery models and rapid prototyping frameworksExperience with AI/ML governance, prompt engineering ...

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 ...

Skills:Hands-on experience with data lineage tools and techniques, including graph & vector databases and metadata management platformsHands-on experience with LLM Ops, MLOps, and AI/ML platform deployment at scaleFamiliarity with business-led analytics delivery models and rapid prototyping frameworksExperience with AI/ML governance, prompt engineering ...

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 ...

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 ...

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 ...

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 ...

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 ...

cases (forecasting, ATP optimisation, document AI, anomaly detection). • Define ML data contracts and embed models in operational processes (Fiori, SAC). • Establish MLOps foundations: pipelines, CI/CD, monitoring, retraining, drift. • Chair the Data & AI Design Authority, driving alignment across internal teams and multiple SI/vendor partners. • Govern ...

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 ...

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 ...

ensuring alignment with enterprise standards and technology strategy.You will also contribute to the evolution of ScottishPower's AI engineering practices, establishing reusable patterns, improving MLOps capabilities and supporting the adoption of modern cloud-native architectures. This includes AI model deployment, monitoring, automation, CI/CD pipelines and responsible AI practices … expertise in Python and modern machine learning frameworks, alongside experience with cloud platforms such as AWS and Azure. Knowledge of LLM frameworks, RAG architectures, MLOps tooling, container technologies and enterprise data platforms will be highly valued.Beyond technical capability, you will be an effective communicator who can influence both technical ...