8 Amazon SageMaker Jobs in the UK excluding London

across one or more CSPs or third-party vendor technologies, including Google PaLM and Vertex AI, Azure OpenAI Services and AzureML, AWS Bedrock and Sagemaker, Dataiku, Databricks, Snowflake SnowPark and Snowflake Cortex, Data Robot.Experience in architecting scalable, performant & cost optimized AI/ML solutions leveraging; serverless technologies, container/ more »

across one or more CSPs or third-party vendor technologies, including Google PaLM and Vertex AI, Azure OpenAI Services and AzureML, AWS Bedrock and Sagemaker, Dataiku, Databricks, Snowflake SnowPark and Snowflake Cortex, Data Robot.Experience in architecting scalable, performant & cost optimized AI/ML solutions leveraging; serverless technologies, container/ more »

engineering practices sch as CI/CD. Experience deploying/monitoring machine learning models and following best practices. The Ability to develop pipelines using SageMaker, MLFlow or similar frameworks. Strong experience with data programming frameworks such as Apache Spark. Understanding of common Data Science and Machine Learning models, libraries more »

emphasis on product development.Experience using computer languages (Python, SQL) to manipulate data and draw insights from large data sets, including cloud-based Snowflake, AWS SageMaker, Azure AI Services and MS Power AppsKnowledge of machine learning techniques (clustering, decision trees, neural networks, graph ML, OCR, sentiment analysis, etc.) and their more »

for everybody. Your responsibilities: Work together with the AI labs, Data, Infrastructure, and Platform teams to design and deploy ML-based services using AWS Sagemaker and other cloud based solutions. Analyse current AWS account setup for data scientists & MLEs and improve it together with StSt MLE & DevOps experts. Understand more »

leading a data science team and managing complex projects. Expertise in machine learning, statistics, data management, and relevant technologies (e.g., Python, R, SQL, AWS SageMaker, Apache Airflow, Dbt, AWS Kinesis). Strong communication skills with the ability to explain complex data concepts to a non-technical audience. Knowledge of more »

different databases. Experience of architecting data solutions across hybrid (cloud, on-premise) data platforms. Knowledge of data science platforms such as Azure Machine Learning, Amazon SageMaker, Databricks, DataRobot, Snowflake etc., to enable the use of data and tie in with roadmap aspirations. Strong knowledge of data modelling, data more »

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