11 of 11 MLOps Jobs in Glasgow

pipelines. Familiarity with data lake architectures and tools like Delta Lake , LakeFS , or Databricks . Knowledge of security and compliance best practices (e.g., SOC2, ISO 27001). Exposure to MLOps platforms or frameworks (e.g., MLflow, Kubeflow, Vertex AI). What We Offer Competitive salary + equity Flexible work environment and remote-friendly culture Opportunities to work on cutting-edge AI More ❯

Senior MLOps Engineer Hybrid/Dundee Salary up to £70,000 We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence. The Role: Managing and optimising existing ML model deployments to ensure reliability More ❯

Trainer/Instructor/Lecturer/Teacher Consultant/Coach/Mentor/Educator ) Ability to explain complex topics clearly and adapt to different learning levels. Familiarity with modern MLOps practices, reproducibility, and collaborative workflows. Practical experience deploying or training models in cloud environments (AWS, GCP or Azure) This is a fully remote working position & salary is £65,000, with More ❯

the BBC. Are you the right candidate? We are open to a range of backgrounds, from ML engineers with hands-on model training and deployment experience, to DevOps and MLOps engineers to strong general software engineers with a real desire to learn about AI. You are encouraged to apply even if you don't meet every one of the criteria … technical team members. Ability to work effectively in a cross functional team. Experience leading technical projects and engaging with stakeholders. A strong interest in AI. Desirable experience: DevOps/MLOps experience, e.g. deploying ML models, setting up training pipelines, model registries, monitoring etc. Hands-on experience training and evaluating ML models. Managing databases and data pipelines. Experience with generative AI. More ❯

data. Collaborate with legal SMEs to translate domain knowledge into scalable machine learning solutions. Continuously evaluate model performance, ensuring accuracy, fairness, and compliance. Help shape the data pipeline and MLOps practices for handling sensitive legal content securely. Required Experience: Solid experience with Python and ML/NLP libraries (e.g., spaCy, Hugging Face, TensorFlow/PyTorch). Experience building NLP or More ❯

centers. We work across the entire spectrum of cloud offerings, from Ubuntu itself to virtualisation and private cloud, Kubernetes, and the implementation of sophisticated open source solutions such as MLops platforms, data platforms and more. We are rapidly expanding the range of open source solutions we offer and deliver to customers, as we move into new industries like telco, finance More ❯

Multipass, Gaming, Enterprise, & Hardware Enablement Ubuntu Pro Services - Our key commercial offerings Ubuntu Pro, Compliance, Standards, Security Engineering, and Managed Services on cloud and on prem AI/ML & MLOps - Open source AI/ML solutions, AIOps automation, model lifecycle management, Kubeflow, MLFlow, KServe, and AI infrastructure on cloud and edge IoT - Ubuntu on embedded devices and/or edge More ❯

to work effectively in a cross-functional team. Desirable experience: Experience on ML projects from inception to delivery. Theoretical understanding of recommender systems. Experience with cloud services, ideally AWS. MLOps knowledge. Understanding of best practices such as testing and code management. About the BBC The BBC is committed to equality of opportunity and welcomes applications from individuals, regardless of age More ❯

AI features, including retrieval-augmented generation (RAG), internal LLM-based tools, and content delivery workflows. Experience with vector stores, agent frameworks, or scalable data workflows is all relevant here. MLOps & Deployment: Build and maintain the infrastructure behind our AI stack – including serving models via APIs, monitoring performance, and deploying systems to the cloud. AWS is a plus, but experience with More ❯

of effective data & analytics delivery models: you have a detailed knowledge of the different delivery and deployment methodologies for data teams, such as agile data product development, AI/MLOps and AnalyticsOps. You will be able to align these methodologies with our clients' objectives and organisational structure, ensuring data teams can be as effective and cost efficient. An understanding of More ❯

Practical and/or theoretical knowledge of Information Retrieval techniques (Recommendations, Search). DESIRED BUT NOT REQUIRED: Experience developing and deploying recommender systems. Experience with model lifecycle management and MLOps, including model deployment, versioning and monitoring. Mentorship of other team members. If you can bring some of these skills and experience, along with transferable strengths, we'd love to hear More ❯