251 to 275 of 463 MLOps Jobs in the UK

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

higher education. Scale platforms and solutions Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g. … with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service bus). Exposure to MLOps and observability tools (e.g., MLflow/model registry, GitHub Actions, Prometheus/Grafana, Evidently AI). Knowledge of integrating with SIS (Banner/Workday Student ...

building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic Claude, Azure OpenAI, and open … databases (SQL Server), data validation, cleansing workflows, scheduling tools (Azure Data Factory), and ensuring data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks ...

building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic Claude, Azure OpenAI, and open … databases (SQL Server), data validation, cleansing workflows, scheduling tools (Azure Data Factory), and ensuring data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks ...

Azure OpenAI, Prompt Engineering, Cognitive Search, Form Recognizer. Data/Coding: Expert-level Python, PySpark, and Vector DB integration. Ops: Practical knowledge of MLOps and LLMOps lifecycles. Security: Must hold active UK Government SC Clearance. Certifications Mandatory: AZ-204 (Azure Developer Associate). Preferred: AZ-305 (Solutions Architect ...

Azure OpenAI, Prompt Engineering, Cognitive Search, Form Recognizer. Data/Coding: Expert-level Python, PySpark, and Vector DB integration. Ops: Practical knowledge of MLOps and LLMOps lifecycles. Security: Must hold active UK Government SC Clearance. Certifications Mandatory: AZ-204 (Azure Developer Associate). Preferred: AZ-305 (Solutions Architect ...

PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able to design and implement MLOps solutions covering many different technologies. Desirable Skills Background in DevOps with exposure to CI systems, e.g. Jenkins Familiarity with infrastructure as code, e.g. Ansible Experience ...

optimisation). Experience leading or managing data scientists on impactful ML/optimisation projects. Excellent Python and SQL skills, with clean, maintainable code. Practical MLOps experience (deployment, monitoring, lifecycle management) in a cloud environment (AWS or similar). Comfortable working with large, imperfect datasets and making sound, pragmatic decisions. Familiarity ...

environments Desirable Experience in highly regulated or safety-critical environments Familiarity with GenAI, LLMs, orchestration frameworks, or agent-based architectures Exposure to data platforms, MLOps, or AI governance Experience working across hybrid or multi-cloud ecosystems Disclaimer: This vacancy is being advertised by either Advanced Resource Managers Limited, Advanced Resource ...

. Practical experience with LLMs, RAG architectures, embeddings and transformers. Experience deploying models using cloud infrastructure and working with microservices or APIs. Familiarity with MLOps concepts such as monitoring, evaluation and continuous improvement. Strong communication skills and the ability to translate business problems into AI-driven solutions. A collaborative mindset ...

Nice to Have Experience in high-growth or early-stage biotech/pharma Familiarity with GxP, HIPAA, or similar frameworks Exposure to data platforms, MLOps, or AI/ML infrastructure in R&D contexts Ownership of SOC 2 or similar certifications Benefits Committed to Care Healthcare, pension/ ...

learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall, F1, Intersection over Union, and others. Additional beneficial ...

learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall, F1, Intersection over Union, and others. Additional beneficial ...

maintain scalable, end‐to‐end AI/ML pipelines using Microsoft Fabric Develop, train, deploy and monitor machine learning and deep learning models Implement MLOps best practices including versioned data and features, CI/CD pipelines , model promotion and rollback . Collaborate with data scientists, analytics engineers, product managers … generation Knowledge of AutoML, hyperparameter optimisation and advanced MLflow features. Experience working with streaming or real‐time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker). Commercial exposure to e‐commerce, travel or holiday‐lettings environments. Experience mentoring others or leading technical ...

MLOps Engineer Location: London, UK (Hybrid - 2 days per week in office) Day Rate: Market rate (Inside IR35 Duration: 6 months Role Overview As an MLOps Engineer, you will support machine learning products from inception, working across the full data ecosystem. This includes developing application-specific data pipelines, building ...

experimental design Experience developing APIs and embedding models within production systems Hands-on experience with cloud-based AI infrastructure and modern LLMOps/MLOps workflows Demonstrated ability to balance speed of delivery with technical excellence Ability to collaborate effectively Ability to communicate effectively If you are interested in this ...

experimental design Experience developing APIs and embedding models within production systems Hands-on experience with cloud-based AI infrastructure and modern LLMOps/MLOps workflows Demonstrated ability to balance speed of delivery with technical excellence Ability to collaborate effectively Ability to communicate effectively If you are interested in this ...

Operations, Digital, Risk). Knowledge of AI governance, risk, compliance, and responsible AI frameworks relevant to FS environments. Exposure to AI delivery teams, including MLOps, data engineering, AI consulting, or agent-development teams. Ability to translate complex technical capability into clear commercial value propositions. Comfortable assessing AI maturity, operating models ...

bonus (linked to MVP pilot) Location: Slough (Hybrid - 2+ days/week) Stack: Python, LangChain, Semantic Kernel, vector DBs, Azure AI/MLOps Visa: No sponsorship available Interested? Please apply below. ...

Python Experience leading teams within SaaS, scale-up or high-growth environments Solid understanding of agile delivery and stakeholder management Exposure to AI, automation, MLOps or agentic AI approaches Comfortable working flexibly to support international customers Benefits: Salary dependent on experience Opportunity to shape engineering strategy within a growing ...