51 to 59 of 59 Azure Machine Learning Jobs in England

Need To Know: Salary: Up to £80,000 per annum Team: Work with cross-functional teams and mentor junior engineers Tools: Microsoft Fabric, Azure ML, MLflow, Spark, Python, SQL, CI/CD, and ML frameworks like TensorFlow, PyTorch, Scikit-learn Scope: End-to-end AI/ML … Grow & Learn, Sustainable Impact. Why join us? Build real-world AI/ML solutions with measurable impact Work hands-on with Microsoft Fabric, Azure ML, Python, Spark & MLflow Collaborate and mentor in a people-first, values-led culture Influence customer experience and commercial decision-making at scale ...

Know: 💰 Salary: Up to £80,000 per annum 👥 Team: Work with cross-functional teams and mentor junior engineers 🤖 T ools: Microsoft Fabric, Azure ML, MLflow, Spark, Python, SQL, CI/CD, and ML frameworks like TensorFlow, PyTorch, Scikit-learn 📊 Scope: End-to-end AI/ML solutions … Grow & Learn, Sustainable Impact. ✨ Why join us? Build real-world AI/ML solutions with measurable impact Work hands-on with Microsoft Fabric, Azure ML, Python, Spark & MLflow Collaborate and mentor in a people-first, values-led culture Influence customer experience and commercial decision-making at scale ...

Experience in the following Implementing AI/ML pipelines for model training, validation, and deployment (using tools such as MLflow, Vertex AI, or Azure ML). Manage model evaluation, drift monitoring, and continuous improvement processes. Optimize inference performance and cost (e.g., model compression, quantization, API optimization). ...

LLaMA, Cohere). Experiment with advanced prompting techniques; Chain-of-Thought, ReAct, Tree-of-Thoughts, and more. Deploy AI/ML pipelines using Azure ML, AWS SageMaker, Vertex AI, or Databricks. Integrate LLMs into production apps using LangChain, LlamaIndex, and RAG architectures. Build APIs and microservices … Stack LLMs: GPT-4/5, Claude, Gemini, Mistral, LLaMA, Cohere Frameworks: LangChain, LlamaIndex, Haystack Tools: GitHub Copilot, Cursor, PromptLayer, Weights & Biases Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks Infra: Python, Docker, Kubernetes, SQL, PyTorch ...

libraries such as spaCy, NLTK, HuggingFace Transformers. • Experience with PDF parsing and text extraction. • Model optimisation and evaluation. • Familiarity with AWS or Azure ML services. ...

SaaS Sales Engineer/Cloud Presales Specialist/AI Presales Consultant/SaaS Integrations/APIs/Security/Compliance/AWS/Azure/GCP/NLP/ML/ISO27001/SOC2/GDPR ...

Cloud Engineering Data Engineering (not building pipelines but designing and building the framework) DevOps MLOps/LLMOps Often work with the following technologies : Azure, AWS, GCP Airflow, dbt, Databricks … Snowflake, etc. GitHub, Azure DevOps and related developer tooling and CI/CD platforms, Terraform or other Infra-as-Code MLflow, AzureML or similar for MLOps; LangSmith, Langfuse and similar for LLMOps The difference to our "AI Engineer" role is: Do you "use/consume" these technologies ...

Technology Product Owner, AI Data Analytics, Microsoft Stack, Azure, Data Engineering, ML, Azure, Mainly Remote Technology Product Owner required to join a global Professional Services business based in Central London. However, this is practically a remote role, but when travel is required (to London … more details... Experience required: Development FIRST mentality. You must have been a Developer before moving into Product Ownership Technical proficiency: Familiarity with Azure services (e.g., Data Lake, Synapse, Fabric) and Databricks for data engineering, analytics, performance optimisation, and governance. Experience with implementing and optimising scalable cloud infrastructure ...

Technology Product Owner, AI Data Analytics, Microsoft Stack, Azure, Data Engineering, ML, Azure, Remote with Travel Technology Product Owner required to join a global Professional Services business based in Central London. However, this is practically a remote role, but when travel is required … more details Experience required: Development FIRST mentality. You must have been a Developer before moving into Product Ownership Technical proficiency:Familiarity with Azure services (e.g., Data Lake, Synapse, Fabric) and Databricks for data engineering, analytics, performance optimisation, and governance. Experience with implementing and optimising scalable cloud infrastructure ...