15 of 15 Contract Azure Machine Learning Jobs in England

Azure ML Ops & Databricks Your responsibilities: Data Analysis & Modeling: Utilize Python for advanced data analysis, exploration, and processing to uncover actionable insights. Develop and implement machine learning models and algorithms using Python , Azure Machine Learning , and Databricks . ML Ops & Deployment: Manage and optimize ML Ops … and validation processes. Platform Expertise: Utilize Databricks for advanced data processing and analytics, ensuring scalability and performance. Continuous Improvement: Stay updated with the latest advancements in data science, machine learning, and cloud technologies to apply best practices. Domain Knowledge: Preferable experience in relevant domain(s) to enhance solution accuracy and business impact. Your Profile Strong proficiency … in Python for data analysis and machine learning. Hands-on experience with Azure Machine Learning , ML Ops , and Databricks . Solid understanding of machine learning algorithms, data modeling, and statistical techniques. Experience in managing large-scale data sets and building scalable solutions. Knowledge of data governance and More ❯

AI Developer - Azure, ML, AI Foundry £Market Rate (Inside IR35) Hybrid/South West London 6 months I am currently recruiting for an AI Developer with expertise in the Microsoft ecosystem, particularly Azure AI services and AI Foundry, to help design, develop, and deploy advanced AI solutions utilising your skills in building scalable AI … with enterprise systems, and leveraging Microsoft's AI tools to deliver business value. Key requirements: Technical Expertise in Azure AI services, Azure Machine Learning (ML), and AI Foundry. Hands-on experience with Azure Cognitive Services, Azure OpenAI, and Azure Data Factory. … Solid programming skills (Python/C#,/.NET) Experience with Azure DevOps, CI/CD pipelines, and GitHub Actions. Knowledge of containerization (tools ie Docker) and orchestration (ie Kubernetes on Azure). Good awareness of Data & AI - understanding of ML lifecycle, MLOps, and Responsible AI. Strong problem-solving and analytical skills. Excellent communication and More ❯

Government agency, working on advanced data and AI-driven solutions to support a mission critical project. This role offers the opportunity to work on cutting-edge initiatives applying Machine Learning, Natural Language Processing, and Large Language Models (LLMs) within a secure environment. Key Skills & Experience: Proven experience as a Data Scientist , ideally in a government or …/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI services). Ability to handle, process, and analyse large, complex datasets. Strong understanding of data ethics, governance, and responsible More ❯

Government agency, working on advanced data and AI-driven solutions to support a mission critical project. This role offers the opportunity to work on cutting-edge initiatives applying Machine Learning, Natural Language Processing, and Large Language Models (LLMs) within a secure environment. Key Skills & Experience: Proven experience as a Data Scientist , ideally in a government or …/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI services). Ability to handle, process, and analyse large, complex datasets. Strong understanding of data ethics, governance, and responsible More ❯

products using Microsoft Azure ML Studio, Python, and Power BI. You will be involved in business conversations to understand requirements, analyse datasets, estimate and productionise machine learning models, and communicate insights to the business using dashboards and storytelling. Key Responsibilities To support the team deliverables, that utilise your expertise to ensure successful outcomes … across team members and collaborating teams * Understand strategic business initiatives and analytical questions to answer. * Design, develop, test, and deploy data science workflows using Microsoft Azure ML Studio with a Python data science stack. * Ensure high-quality delivery of accurate data science models, and review that proposed solutions meet security, compliance, and governance requirements. * Monitor model performance … pandas, numpy, etc) * Understanding of data science concepts, AI/ML models, evaluation approaches, and data science applications to enhance business processes * Proven hands-on experience in Microsoft Azure ML Studio * Experience using business intelligence tools, preferably Power BI * Experience applying Generative AI and prompting techniques * Strong understanding of data governance, model observability, and compliance frameworks * Proven More ❯

3.x, Gemini 2.x, Mistral Large, LLaMA 3, Cohere Command R+, DeepSeek Frameworks: LangChain, LlamaIndex, Haystack, AutoGen, CrewAI Tools: GitHub Copilot, Cursor, LangSmith, LangFuse, Weights & Biases, MLflow, Humanloop Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks, Modal Infra: Python, Docker, Kubernetes, SQL/NoSQL, PyTorch, FastAPI, Redis More ❯

Qualifications: • 6+ years of experience in applied data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python More ❯

following core areas: Model Lifecycle Management (MLOps): Proven experience in implementing robust AI/ML pipelines for model training, validation, and deployment (e.g., using MLflow, Vertex AI, or Azure ML). Expertise in managing model evaluation, drift monitoring, and continuous improvement processes. Strong focus on optimizing inference performance and cost (e.g., model compression, quantization, API optimization). More ❯

following core areas: Model Lifecycle Management (MLOps): Proven experience in implementing robust AI/ML pipelines for model training, validation, and deployment (e.g., using MLflow, Vertex AI, or Azure ML). Expertise in managing model evaluation, drift monitoring, and continuous improvement processes. Strong focus on optimizing inference performance and cost (e.g., model compression, quantization, API optimization). More ❯

and secure AI service architectures. Required Experience/Skills: 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). Ensure compliance with AI ethics More ❯

and secure AI service architectures. Required Experience/Skills: 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). Ensure compliance with AI ethics More ❯

/5, Claude, Gemini, Mistral, 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 for scalable AI deployment. Use AI … ML or related field. Tech 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 More ❯

frameworks , is essential. This role demands both technical depth and excellent communication skills to engage with business stakeholders, design scalable AI systems, and ensure reliable model deployment using Azure and Databricks. Key Responsibilities Lead end-to-end AI experimentation processes from conceptualization to deployment. Collaborate with business stakeholders to define success metrics, KPIs, and measurable outcomes for … Flow, AI component selection, Prompt Engineering, AP, I, and AI integration planning) Automated model evaluation and monitoring frameworks Design, build, and scale data pipelines and AI workflows on Azure and Databricks ecosystems. Apply Generative AI techniques for text, code, image, and multi-modal use cases using advanced prompt engineering. Utilize modern GenAI toolkits and libraries, including: PyTorch … in Applied data science. with at least 2+ years focused on Generative AI/LLMs . Strong experience in Databricks data engineering and ML workflows. Proficiency in the Azure AI/ML ecosystem , including MLOps and data management best practices. Demonstrated expertise in: Python (advanced) AI/ML libraries (PyTorch, Hugging Face, Scikit-learn, TensorFlow, optional) Prompt More ❯

Role/Job title Data Scientist - Azure ML Ops & Databricks Work Location Wokingham, UK Role type - Permanent/Fixed Term/Contracting Contracting Mode of working Hybrid/office based Office based 5 Days in Office If Hybrid, how many days are required in office? NA Number of positions 1 Duration of assignment 06 Months Any other More ❯

the dataset Running experiments to compare model versions, test different approaches and prove which solution gives the best long term stability Deploying and monitoring the improved model in Azure so it runs reliably day to day Working closely with engineering to streamline the end-to-end pipeline, from data ingestion through to model output Putting proper monitoring … to be strong across modelling libraries, experimentation and writing clean code that the team can maintain. You'll be rebuilding parts of the pipeline, not just tweaking notebooks. Azure You'll be using Azure ML, pipelines, storage and deployment tools to get this model stable in production. If you've moved models from local … development to Azure based production before, this is exactly that kind of work. Forecasting and predictive modelling This project needs someone who has solved real business forecasting problems. If you've fixed models suffering from drift, poor generalisation, weak features or inconsistent performance in live environments, you'll fit straight in. This is for someone who enjoys More ❯