24 of 24 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 ...

Relevant cloud, AI, or security certifications Experience deploying ML models into production environments Experience with Kubernetes, OpenShift, or cloud-native deployment architectures Experience with MLOps tooling (e.g. MLflow, Kubeflow, model monitoring platforms) Experience applying DevSecOps practices within cloud or controlled environments Exposure to large language models or generative AI systems ...

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 ...

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 ...

flows and lifecycle management from ingestion to consumption. Enable Advanced Analytics & ML Partner with the data science and software development teams to establish strong MLOps and DataOps practices. Support geospatial and large‐scale analytical workloads. Ensure data is discoverable, reusable, and fit for experimentation and production ML. Governance & Client Engagement ...

agile delivery environmentStrong problem‐solving skills and attention to detailDesired Skills:Experience with cloud‐based ML services (AWS SageMaker, Azure ML, Databricks)Familiarity with MLOps practices and model lifecycle managementExperience with NLP, deep learning, or computer visionKnowledge of data visualisation tools (Power BI, Tableau)Exposure to big‐data technologies (Spark ...

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 ...

areas, and encourage anyone with the experience listed above to apply. We would particularly like to encourage applicants with experience in the following areas: MLOps: including tools like LangChain for application development and managing the ML lifecycle Data Engineering: including platforms like Databricks for data processing and analytics DevSecOps & DevOps ...

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. Bachelor/Master's/PhD or equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field. Desirable Experience with MLOps pipelines, model deployment, or production ML systems. Familiarity with performance analysis, profiling tools, or numerical accuracy validation. Exposure to distributed training or inference systems. Experience ...

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 ...

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 ...

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 ...

Mathematics or Data Science Commercial experience delivering ML solutions Good Python skills In depth knowledge of AI/ML Experience developing ML pipelines with MLOps Cloud & Linux experience would be beneficial but not essential Security Clearance Eligibility for Security Clearance is required for this role Apply To apply, follow ...

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 ...

Strong working knowledge of ISO 27001 (Information Security Management) and ISO 42001 (Artificial Intelligence Management System). Hands-on understanding of data management principles, MLOps lifecycles, and model auditing. Must have active UK SC clearance (or active DV clearance). #J-18808-Ljbffr ...

across both software development and infrastructure. You’ll enjoy solving complex technical challenges, working in dynamic environments, and collaborating closely with Data Scientists and MLOps teams. A pragmatic, adaptable mindset is key, along with a passion for building scalable, secure systems that enable data‐driven outcomes. You should also … data management initiatives. Develop, test and deploy new platform capabilities. Troubleshoot and enhance existing analytics services. Provide hands‐on support to Data Scientists and MLOps teams. Tackle complex engineering challenges across a varied tech stack. Requirements: Strong experience with Python. Experience with Kubernetes and Docker. Understanding of CI/ ...

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 ...

NLP PEOPLE is seeking a leader for the Machine Learning Engineering team in Bristol. This hybrid role involves guiding the operation of AI/ML services, ensuring robust governance and stakeholder engagement. The ideal candidate ...

Responsibilities Lead the Machine Learning Engineering team in the safe and effective operation of AI/ML products and services in production, maximising the value and adoption of data‐driven decision making across the business. ...