14 of 14 Permanent MLOps Jobs in the South West

pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs, generative AI, and prompt engineering. Knowledge of MLOps tools and frameworks (MLflow, Kubeflow, Airflow). Familiarity with SQL, NoSQL, and distributed data technologies. Experience deploying AI models in production environments. Publications, patents, or open-source contributions ...

native data services and event-driven architectures Experience building data products that support analytics, reporting, machine learning, or AI use cases Knowledge of MLOps, AI Engineering, Agentic AI, or Generative AI implementation patterns Experience leading distributed engineering teams Experience establishing engineering standards, reusable frameworks, and community-of-practice initiatives Knowledge ...

infrastructure for latency, scalability, and cost. Build infrastructure to monitor model performance, data drift, and other key metrics in production. Collaborate with Devlopers and MLOps engineers to ensure that pipelines are production-ready. Implement security, compliance, and governance practices. Support troubleshooting and incident response for deployed systems. Building relationships with ...

analytics Delivering production agentic systems, including RAG pipelines, vector search, and agentic frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, and n8n DevSecOps & DevOps MLOps Infrastructure as Code Building a truly diverse, equitable, and inclusive workplace is an ongoing journey, and were excited to keep learning and growing together. We have ...

skills Experience with Linux operating systems (e.g. Red Hat, Ubuntu) Experience working within a variety of development frameworks and practices e.g. DevOps, DevSecOps, SCRUM, MLOps, XP. Experience with data analysis and manipulation tools (e.g. Pandas) Experience of a broad section of the Software Development Lifecycle (SDLC) with specific focus ...

using LLMs and emerging AI technologies. * Support autonomous capabilities using ROS 2 and similar frameworks. * Implement robust software engineering, testing, CI/CD and MLOps practices. * Support bids, demonstrations, workshops and customer engagements. * Ensure adherence to Responsible AI, cyber security and safety standards. Essential Experience Experience delivering ...

Knowledge of C++, Python, PyTorch, OpenCV, CUDA, TensorRT, Git, WSL, Docker, Jira/Confluence Machine Learning and Deep Learning Computer Vision methodologies and algorithms MLOps Developing AI for use on Edge Computers Research and prototyping Benefits: Annual Company Bonus – Based on company performance 25 Days holiday not including bank holidays ...

tested, and well-documented code suitable for long-term ownership and handover. Hands-on experience with production infrastructure, including Docker, Linux, CI/CD, MLOps, cloud platforms, and model serving architectures. Be able to work with state-of-the-art ML libraries to deliver powerful results quickly. Comfortable working ...

Productionise PoC/PoV work into hardened solutions with clear non-functional requirements (performance, resilience, cost, security) and defined service ownership Build and maintain MLOps/LLMOps pipelines (CI/CD, automated testing, packaging, promotion/rollback, model/version management) to enable repeatable releases Develop reusable engineering assets (libraries … experience with AI deployment patterns and infrastructure (e.g. containerisation with Docker, orchestration such as Kubernetes, API-based serving, batch/stream inference) Practical MLOps experience: CI/CD for ML, model packaging and release management, automated validation, monitoring, and lifecycle management Working knowledge of ML/DL frameworks and tooling ...

appropriate performance metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...

appropriate performance metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...

appropriate performance metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...

role in designing, building, testing and evolving scalable analytics hosting platforms, while also providing hands-on engineering support to Data Scientists and MLOps teams. The role offers plenty of variety, with the opportunity to work across a broad range of technologies and tackle complex technical challenges. You'll need … across existing analytics services. Deliver bug fixes and feature enhancements for mission-facing analytics platforms. Provide hands-on engineering support to Data Scientists and MLOps teams. Work across a varied technology landscape, adapting to unfamiliar technologies where required. Contribute to the design and implementation of reliable, scalable and secure technical ...

will develop, test, deploy, and enhance platform capabilities, resolve issues within existing analytics services, and provide hands-on engineering support to Data Scientists and MLOps teams working across a range of technologies. You will operate in a dynamic environment with varied and sometimes unfamiliar technical challenges, requiring strong problem-solving … lifecycle. Design, develop, test, and deployment of a new analytic hosting platform. Bugfixes and feature requests for existing mission facing analytics. Engineering support to MLOps engineers and Data Scientists. These are unpredictable and highly variable requirements, potentially using unfamiliar technology, so a flexible style is required. In this role ...