1 to 25 of 31 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 ...

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 ...

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 ...

operations for data manipulation and analysis. You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases). You have good understanding of MLOps practices and model deployment workflows. You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain). Your level of English is advanced (C1) or above. ...

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 ...

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 ...

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 ...

guide and coach the team Excellent Python coding practice, including ML libraries such as HuggingFace, TensorFlow and PyTorch Experience building robust ML pipelines with MLOps tools for model training, monitoring and deployment Experience with version control and environment management (e.g. venvs, Docker) Expert knowledge of AI/ML algorithms across ...

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 ...

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 ...

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 ...

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 ...

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 ...

commercial deployment, focusing on performance, reliability, and maintainability. Key qualifications include expertise in TensorFlow and Python, experience in API development, and familiarity with MLOps practices. Joining means working on cutting-edge ML solutions and collaborating with experts across various fields. #J-18808-Ljbffr ...

Purview, Azure ML, Databricks, MLflow or Microsoft Fabric . Knowledge of DAMA-DMBOK, NIST AI RMF, ISO 23894, ISO 27001 or UK GDPR . MLOps, model monitoring or AI risk/control experience. Benefits: Salary up to £80,000 25 days holiday + bank holidays Private Medical Insurance Hybrid working ...

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/ ...

integration between connected devices, cloud services, data platforms, and engineering teams. As the capability matures, the role will provide a clear development path into MLOps and ML platform engineering, supporting model deployment, model lifecycle controls, ML pipeline automation, and governed promotion of machine learning solutions from development into production. … validation, monitoring, transformation and handover between operational platforms and analytical environments. Proactively identify opportunities to simplify, automate and strengthen digital platform delivery. Growth into MLOps and ML platform engineering Develop capability in MLOps practices such as experiment tracking, model packaging, model registry, model promotion and governed deployment workflows. Support ...

design, build, and evolve scalable analytics platforms, supporting the full lifecycle from development to deployment and optimization. Work in collaboration with Data Scientists and MLOps to tackle complex challenges across a modern stack, including cloud migration, and data management, in a hybrid UK setting with #J-18808-Ljbffr ...

connected products and industrial IoT capabilities. Initially focus on DevOps, cloud operations, IoT data flows, deployment automation and environment management, with a path into MLOps and ML platform engineering as capability matures. #J-18808-Ljbffr ...