26 to 34 of 34 Permanent Amazon SageMaker Jobs

ability to design scalable, cloud-native machine learning operations across traditional ML and modern LLM workflows. The ideal candidate will bring experience with SageMaker-based MLOps pipelines, evaluation of equivalent tooling stacks, hybrid MLOps/LLMOps automation, CI/CD orchestration, governance, monitoring, automation and production-grade scalability patterns. … deployment, versioning, monitoring, and CI/CD automation. Build container-oriented ML platforms (EKS-first) while evaluating alternative orchestration tools with similar capabilities (Kubeflow, SageMaker, MLflow, Airflow, etc.). Implement hybrid MLOps + LLMOps workflows, including prompt/version governance, evaluation frameworks, and monitoring for LLM-based systems. Serve ...

system performance using CloudWatch metrics, alarms, and logs; troubleshoot proactively. Develop, deploy, and optimize AI/ML solutions using AWS AI services including SageMaker and Bedrock, supporting model training, inference, and integration into production systems. Automate operational tasks using AWS Lambda, Systems Manager (SSM), and Infrastructure-as-Code tools … PySpark); strong understanding of data architecture and ETL/ELT patterns. 4 years of experience working with AWS AI/ML services such as SageMaker, Bedrock, and vector databases (OpenSearch). Strong understanding of machine learning algorithms, NLP concepts, and deep learning frameworks such as TensorFlow, PyTorch, or Hugging ...

rich metadata, automated quality profiling, and governance guardrails. Consumers: Reduce friction from discovery to access — self-service provisioning, entitlement workflows, one-click integration with SageMaker, Databricks, and EMR. Network effects: Analyze usage trends to improve data quality, discovery and relevancy across persona groups Collaborate with Engineering, Design & Data Science ...

production-ready systems. Perform feature engineering, data preprocessing, model selection, hyperparameter tuning, and performance optimization. MLOps & Productionalization Develop and maintain ML pipelines using AWS SageMaker, MLflow, H2O.ai, and other automation tools. Implement best practices for model versioning, lineage tracking, model performance monitoring, and retraining. Set up CI/… pipelines for ML services and automate deployment workflows. Cloud & Distributed Systems Architect and operate scalable ML workflows in AWS, including SageMaker, Step Functions, S3, ECR, CloudWatch, IAM, etc. Build and optimize distributed data processing pipelines using PySpark and AWS EMR. Ensure reliability, scalability, and cost efficiency of ML environments. ...

data platform architecture • Define governance, data modelling, and information architecture standards • Lead selection and implementation of AI technologies (AWS stack including Bedrock, SageMaker, Amazon Q) • Partner with senior stakeholders across data, engineering, and business functions • Guide a small team and work with external delivery partners We’re looking ...

solutions to effectively scale and maintain the data platform. You will tackle complex data challenges in a fast-paced, exciting environment, leveraging cutting-edge Amazon Web Services (AWS) technologies such as Lambda, SageMaker and Bedrock to develop innovative and scalable data solutions. After a suitable settling in period ...

solutions to effectively scale and maintain the data platform. You will tackle complex data challenges in a fast-paced, exciting environment, leveraging cutting-edge Amazon Web Services (AWS) technologies such as Lambda, SageMaker and Bedrock to develop innovative and scalable data solutions. After a suitable settling in period ...

governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift … closely with Engineering/Data teams in production-first environments Comfortable operating within regulated industries Desirable AWS experience (S3, Athena/Glue, IAM, Lambda) SageMaker or equivalent ML platform experience Financial services domain knowledge (risk, fraud, affordability, payments) Experience with model explainability and governance documentation Package & Benefits Hybrid working ...

Join Ligentia! We’re on a mission to move away from fragmented, manual reporting and create a standardised, global "single source of truth" for customer data. We’re looking for an adaptable and dynamic Customer ...