4 of 4 Remote/Hybrid Azure Machine Learning Jobs in Bristol

build and deploy AI/ML-enabled solutions: Enable feature-ready, governed datasets for data science and integrate with Azure Machine Learning and Fabric experiences to operationalise models and drive business insights. Design, monitor and optimise data pipelines and platform performance: Use Fabric … Data Factory, Microsoft Fabric (Lakehouse/Warehouse), and strong understanding of data warehousing, dimensional modelling, and lakehouse concepts. Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage/ADLS Gen2, Microsoft Fabric (OneLake, Workspaces, Capacity), Azure Synapse ...

systems to Data Warehouses, Data Lakes, and Lake Houses using Open Source and cloud tools. Build and deploy AI/ML models: Integrate Machine Learning into data pipelines, leveraging ML to develop predictive models and drive business insights. Monitor and optimize data pipelines and infrastructure: Analyze … insights. Proven expertise in Databricks, Apache Spark, and data pipeline development and strong understanding of data warehousing concepts and practices. Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks and Azure Data Factory. Azure Data ...

data quality checks, and governance practices to ensure reliable and accurate data. Ability to Design, Build and deploy AI/ML models: Integrate Machine Learning into data pipelines, leverage Databricks ML and Azure ML to develop predictive models and drive business insights. Design … solutions Proven expertise in Databricks, Apache Spark, and data platforms with a strong understanding of data warehousing concepts and practices. Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks, and Azure Data Factory. Excellent problem-solving and analytical ...

recruiter directly. About the Role Lead AI Engineer We’re seeking a Lead AI Engineer who can design, build, and operationalise advanced AI, Machine Learning, and Generative AI systems at enterprise scale. The focus of this role is to bridge the gap between AI prototypes … teams to execute complex requirements Architecting and implementing Generative AI solutions, including RAG pipelines, agentic workflows, and orchestration of large language models across Azure, GCP, or AWS. Embedding safety, evaluation, and assurance mechanisms across the AI lifecycle, ensuring solutions are ethical, explainable, and responsible. Collaborating with Product ...