23 of 23 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 ...

PyTorch, or Java-based ML libraries) Strong problem-solving and communication skills Preferred Qualifications Experience with NLP, computer vision, or recommendation systems Familiarity with MLOps practices and model lifecycle management Knowledge of event-driven architectures (Kafka or similar) Experience with DevOps tooling and infrastructure as code Exposure to Generative ...

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 ...

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 ...

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

working with cloud-based machine learning and data platforms, including technologies such as Vertex AI, BigQuery, Cloud Run or equivalent cloud services.Practical experience implementing MLOps tooling and frameworks such as Kubeflow Pipelines, dbt or similar solutions, including monitoring and operationalising large-scale models.Experience working with Infrastructure as Code, Kubernetes ...

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 ...

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 ...

development and deployment of ML and AI models to prove and deliver tangible commercial value. Act as a technical bridge between Data Science and MLOps to embed best practice deployment techniques across the team. Take hands-on ownership of big projects, working with a large, event-based data set. Research ...

data platforms.Design and implement reusable data products, semantic models and analytics capabilities that support reporting, machine learning and GenAI workloads.Drive adoption of AI Engineering, MLOps and LLMOps best practices across development, deployment, monitoring and governance.Champion security, resilience, privacy, Responsible AI and governance by design.Identify opportunities to improve efficiency, reliability … cases.Understanding of modern GenAI architecture patterns including vector databases, retrieval-augmented generation (RAG), embeddings, agentic workflows and LLM orchestration frameworks.Knowledge of MLOps, model lifecycle management, observability and AI governance practices.Experience with cloud platforms such as GCP, Azure or AWS and associated platform services.Strong understanding of containers, Kubernetes, CI/ ...

including machine learning models, data pipelines and application components that are secure, reliable and performant.Drive the operationalisation of AI solutions using modern engineering and MLOps practices, including CI/CD, model monitoring, testing and lifecycle management.Ensure solutions are developed in line with security, privacy, governance and responsible AI requirements, particularly … practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation approaches.Experience with MLOps and modern engineering practices, including CI/CD pipelines, model versioning, monitoring and automated testing.Experience deploying AI solutions on cloud platforms such as Azure ...

Service and AI platform solutions in hybrid or managed service environments, including familiarity with agentic AI systems, multi-agent orchestration, and AI lifecycle frameworks (MLOps, LLMOps, DataOps). Proven presales experience with strong communication and stakeholder engagement skills , able to articulate complex technical solutions, integrate cloud-native AI services ...

Allianz UK Personal is looking for a Lead Data Engineer (MLOps) to further enhance our MLOps capability.Where and how you can workThis is a hybrid role at one of our offices in London, Bristol or Bournemouth and you’ll be required to come into the office two days per month.Salary … total reward package.About the teamYou’ll join an agile, stream-aligned team, working with technical and business stakeholders to deliver Data Science & MLOps products that drive commercial value.The team is ambitious – continuously raising the bar on what our products can deliver for the business and our customers.About the RoleWe ...

Allianz UK Personal is looking for a Lead Data Engineer (MLOps) to further enhance our MLOps capability.Where and how you can workThis is a hybrid role at one of our offices in London, Bristol or Bournemouth and you’ll be required to come into the office two days per month.Salary … total reward package.About the teamYou’ll join an agile, stream-aligned team, working with technical and business stakeholders to deliver Data Science & MLOps products that drive commercial value.The team is ambitious – continuously raising the bar on what our products can deliver for the business and our customers.About the RoleWe ...

multi cloud with strong AWS depth). Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components). Proven ability to take research and prototype environments ...

hypothesis development, testing and evaluation Transition successful models from proof of concept into production environments Develop scalable ML pipelines using AWS cloud technologies Implement MLOps and LLMOps best practices for deployment, monitoring and governance Support feature engineering, model optimisation and performance monitoring Apply responsible AI principles, including model explainability … Python Experience with frameworks such as PyTorch, TensorFlow, Scikit-learn or XGBoost Knowledge of AWS cloud services including SageMaker, Lambda and S3 Experience with MLOps tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge of Generative AI, LLMs, prompt engineering ...

agentic workflow capabilities for legal content products. In addition to writing code on complex systems, this position provides technical direction on architecture, MLOps, responsible AI, legacy system integration, AWS-based delivery, and AI-assisted development practices. The position does not have direct reports. Key Responsibilities:Serve as the initial point … accuracy, groundedness, citation quality, hallucination risk, agent task success, latency, cost, reliability, and business value.Successfully implement development processes, coding best practices, code reviews, MLOps practices, and responsible AI controls.Apply AI-assisted development tools to reduce software development cycle time and support code explanation, test generation, refactoring, debugging, documentation, code review ...

Engineering: Deep prompt engineering & optimization skills for GenAI.Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI (RAG) for knowledge applications.GenAI ModelOps/MLOps & Governance: GenAI ModelOps/MLOps knowledge with ethical AI governance focus.Multimodal & Code Generation: Architected GenAI for multimodal (vision, audio, language) & code generation.ER&I GenAI Applications ...

test and deploy machine learning models, analytical pipelines and data science components that are robust, scalable and maintainable.Support the operationalisation of ML solutions through MLOps practices, including model monitoring, versioning, automated testing, CI/CD and performance optimisation.Apply responsible AI, model explainability, security, privacy and governance considerations throughout the development … PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and optimisation.Understanding of MLOps and production ML practices, including CI/CD, model versioning, automated testing, retraining, monitoring and reproducible delivery.Experience using cloud platforms and data science environments such ...

leaders. You are aligned and accountable.You are comfortable with ambiguity, fast cadence, and ownership. Excuses do not ship parts. Execution does.You have MLOps and production deployment experience at scale.Great plus:Background in composites, advanced manufacturing, aerospace, automotive, or defense.Experience with computer vision applied to automated inspection, generative design, reinforcement learning ...

data solutions. This role will see you building and maintaining scalable platform capabilities, troubleshooting existing services, and providing technical support to Data Scientists and MLOps teams working across a range of technologies. Key Responsibilities of the Analytics Platform Engineer Design, build and maintain scalable analytics platforms and cloud-based infrastructure. … platform capabilities while enhancing and maintaining existing analytics solutions. Troubleshoot technical issues, implement improvements and optimise platform performance. Collaborate closely with Data Scientists, MLOps Engineers and other technical teams to deliver reliable, secure and high-performing solutions. Adapt to a varied workload, solving complex engineering challenges across a range ...

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 ...

cloud migration, analytics platforms, and data-driven solutions. This is an excellent opportunity to work on mission-critical systems, supporting Data Scientists and MLOps teams while helping to design, build and evolve a scalable analytics hosting platform. Start Date: ASAP Job Type: Contract or Permanent Duration: 2 Months Initially … across the full software development life cycle, delivering platform enhancements, resolving issues within existing analytics services, and providing engineering support to Data Scientists and MLOps teams. Key Responsibilities: Designing, developing, testing and deploying a new analytics hosting platform Supporting cloud migration and data management initiatives Building scalable, secure, and resilient ...