7 of 7 Permanent MLOps Jobs in Dorset

with call/contact-centre analytics, Microsoft Teams Graph API, or telephony platforms (BroadWorks, Webex Calling). Knowledge of data governance, model ethics, and MLOps practices. Exposure to data visualization and predictive analytics for customer-experience metrics. Advanced degree in AI, ML, Data Science, or related discipline. ISTQB AI Testing ...

pipelines Partner closely with data scientists and engineers to keep AI systems stable and fast What you bring Strong background in AI Ops, MLOps, DevOps or Infrastructure Engineering Hands-on experience with Linux, automation, scripting (Python/Bash) Experience with distributed systems and compute-heavy environments Familiarity with containers & orchestration ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

maintain machine learning models, especially Large Language Models (LLMs), in production environments. If you have solid DevOps experience and are keen to grow your MLOps skills, we'd love to hear from you! What You'll Be Doing: Automating Machine Learning workflows (training → deployment) with AWS & GitOps Deploying LLMs using … Developing production-grade APIs (REST/gRPC) to serve models Collaborating with engineers, data scientists & DevOps teams Your Experience: Industry experience in DevOps or MLOps roles (ideally in AWS environments) Hands-on with Docker, Kubernetes, and Terraform Strong scripting skills in Python or Bash Familiar with ML lifecycle tools, model ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

doing Designing and building production ML systems and pipelines in Python Architecting scalable inference infrastructure and model serving systems Building robust MLOps tooling for training, evaluation, and deployment Owning AI system reliability, performance optimization, and monitoring at scale Acting as a technical leader within the AI engineering team, with … Python skills with deep ML frameworks experience (PyTorch, TensorFlow, or similar) Proven experience running production ML systems at scale Strong background in model deployment, MLOps, and ML system architecture Experience with LLMs, transformers, or modern AI architectures Comfortable making long-term technical decisions around ML infrastructure Experience in regulated ...

Captur helps software understand real world scenes in real-time with an SDK for flexible, on-demand visual recognition. We're a small, rapidly scaling team backed by top-tier investors; we recently closed a ...