1 to 25 of 40 Permanent MLOps Jobs in the South West

.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 ...

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 ...

Intelligence, Data Science, or a related technology discipline Minimum 2:1 degree classification (or equivalent) Desirable Azure OpenAI, AWS Bedrock and Google Gemini experience MLOps, Data Engineering or Platform Engineering experience Experience leading technical teams Knowledge of Agentic AI, AI Agents and emerging AI frameworks What's On Offer? Opportunity ...

equivalent platforms.Developing high-quality, maintainable code and working with software engineering practices such as version control, testing, code review and CI/CD.Working with MLOps or workflow tools such as MLflow, Kubeflow, Argo or equivalent frameworks.Scaling models or analytical services for enterprise or operational use.Applying statistical methods, model evaluation techniques ...

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 ...

Learning Applied machine learning, computer vision, object detection, image classification, model development and evaluation, data annotation and curation, training pipelines, performance optimisation, edge ML, MLOps, deployment and maintenance of ML solutions, Python development, Python‐based ML frameworks, PyTorch, TensorFlow, sklearn, OpenCV, NumPy, feature development, code review, pytest, linting, bug fixing ...

Data Engineering - Python, SQL, ETL/ELT, modern cloud data platforms, Spark/Databricks and data architecture AI & Machine Learning - ML Engineering, MLOps, Python, model deployment, evaluation, LLM/GenAI and production AI Technical Leadership - Senior/Lead engineering roles across Cloud, Platform, Data and AI The organisations vary ...

internal stakeholders.** *Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.** *Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.** *Experience of appropriate version control and environment management (such as venvs or Docker).** *Experience of writing technical project ...

customers and internal stakeholders.Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.Experience of appropriate version control and environment management (such as venvs or Docker).Experience of writing technical project proposals.Experience ...

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 ...

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 ...

performance and cost-effectiveness. AI: Develop and deploy AI/ML models into production environments. Build scalable inference pipelines and AI APIs. Implement MLOps workflows for model versioning, monitoring, and retraining. Collaborate with data scientists to productionize machine learning solutions. Evaluate and optimize AI model performance and operational efficiency. Database ...

fundamentals. Applied machine learning, computer vision, object detection, image classification, model development and evaluation, data annotation and curation, training pipelines, performance optimisation, edge ML, MLOps, deployment and maintenance of ML solutions, Python development, Python-based ML frameworks, PyTorch, TensorFlow, sklearn, OpenCV, NumPy, feature development, code review, pytest, linting, bug fixing ...

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 ...

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 ...

Event Hubs, or Kinesis for real-time data processing Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines Experience processing and managing unstructured data types (text, images, logs, sensor data) Understanding of Lambda and Kappa architectural patterns and when to apply each ...

/etc.) Genuine enthusiasm for AI-assisted development (LLMs/agents as core tools) Nice to have: regulated-environment experience, AI safety involvement, MLOps/CI/CD depth. If you think this role would be a good fit for you, please reach out to Charles Duran. ...

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 ...

More about the roleWe are looking for a Mid-Level Data MLOps Engineer to operationalise, scale, and maintain our machine learning models in production. In this role, you will build and automate the infrastructure that powers our retail ML initiatives, from demand forecasting and inventory optimization to personalized customer loyalty … inference latency to ensure production retail models remain accurate and reliable.More about youRequired Skills & QualificationsExperience: 3 to 5 years of production experience in an MLOps, DevOps, or Machine Learning Engineering role focused on productionising models.Programming: Professional-level proficiency in Python, with a deep understanding of writing clean, modular, and testable ...

C#/.NET services. Performance & Scalability : Optimize GPU/CPU utilization, batching strategies, and memory management. Plan for multi-model and multi-tenant scenarios. MLOps & Lifecycle Management : Implement model versioning, artifact registries, and deployment workflows. Set up monitoring, logging, and alerting for solver performance. Security & Compliance : Apply best practices ...

Strong architectural capability across cloud-native systems, distributed design, integration patterns and enterprise platforms. Practical experience delivering AI/ML systems into production, including MLOps, model evaluation, monitoring and safety considerations. Familiarity with agentic coding systems (Claude Code, PI, MCP tools) and how they operate within real engineering environments. Ability ...

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 ...