1 to 25 of 67 MLOps Jobs in Scotland

.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 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 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/ ...

optimize relational data models using PostgreSQL. Deploy and manage backend services on cloud platforms, preferably Azure and/or GCP. Collaborate with DevOps/MLOps engineers on CI/CD pipelines, containerization, and deployment strategies. Monitor service health and performance, proactively addressing bottlenecks and reliability issues. Work within an Agile ...

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 ...

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. ...

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 #J ...

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 ...

Skills: Hands-on experience with data lineage tools and techniques, including graph & vector databases and metadata management platforms Hands-on experience with LLM Ops, MLOps, and AI/ML platform deployment at scale Familiarity with business-led analytics delivery models and rapid prototyping frameworks Experience with AI/ML governance ...

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 ...

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 ...

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 ...

curiosity to learn others. Bridging Data & AI: Understanding how AI fits into the broader data landscape, interest in integrating LLMs and AI/MLOps into client solutions. Collaborative Leadership: Proven track record of supporting multi-squad deliveries, guiding stakeholders through architectural trade-offs, and contributing to technical proposals. Our Benefits ...

Skills: Hands-on experience with data lineage tools and techniques, including graph & vector databases and metadata management platforms Hands-on experience with LLM Ops, MLOps, and AI/ML platform deployment at scale Familiarity with business-led analytics delivery models and rapid prototyping frameworks Experience with AI/ML governance ...

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 ...

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 ...