7 of 7 Remote/Hybrid Amazon SageMaker Jobs in London

tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience (AWS, GCP, Azure), containerisation and basic data engineering/SQL Familiarity with experimentation, A/B testing and online evaluation ...

with the Data Engineering and AI Platform teams, you will drive excellence and pace in the build, deployment, testing, and monitoring of models using Amazon Sagemaker [and occasionally Snowflake] Causal Inference & Decision Science: Lead the development of advanced causal models (e.g., Media Mix Modelling, retention drivers, and simulation ...

content classification, synthetic panels, model validation). Experience with data platforms such as Databricks, snowflake or other cloud native solutions (GCP big query, AWS sagemaker). Solid understanding of agile practices. Any experience in SAFe is considered a plus. How we work Fifty5Blue’s core values are: Clarity, Independence ...

models influence real lending decisions and commercial outcomes Experience deploying and maintaining models within production environments Strong Python, SQL and AWS experience (particularly SageMaker and Lambda) Comfortable working in a fast-moving, hands-on environment with high ownership Excellent communication skills with both technical and business stakeholders What ...

demonstrate excellent technical capabilities, including proficiency in Python, SQL and Git. Practical experience deploying machine learning models within cloud-based environments, particularly using AWS SageMaker, will be highly advantageous. Candidates should possess a solid understanding of statistical modelling techniques and demonstrate a genuine enthusiasm for machine learning, predictive analytics ...

models including scorecards, behavioural, acquisition and fraud models Build predictive models using advanced statistical and machine learning techniques Deploy models into production using AWS SageMaker and collaborate with engineering teams Monitor model performance and ensure ongoing effectiveness across business and technical metrics Generate insights and present clear, actionable recommendations ...

models and drive business insights.Be a Databricks champion or have some Databricks certificationsAWSWork hands-on with AWS services such as Redshift, Glue, Lake Formation, SageMaker, Athena, and moreStrong hands-on expertise with AWS services (e.g. Redshift, Glue, Lake Formation, SageMaker).AWS Certified ArchitectAdditional InfoSecurity Clearance: To be successfully ...