1 to 25 of 37 Remote/Hybrid 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 ...

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 ...

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 ...

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 ...

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 ...

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. ...

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 ...

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 ...

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 ...