10 of 10 Remote/Hybrid Permanent Amazon SageMaker Jobs

Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure ...

technical direction. End-to-End AI Delivery: Design, build, and maintain scalable AI and LLM-based pipelines using AWS or Azure services (e.g., SageMaker, Azure ML, Databricks, OpenAI integrations). Contribute across AI model lifecycles from data preprocessing and prompt engineering through to deployment and continuous monitoring in production ...

instances, and Kubernetes clusters Provision and configure storage, networking, and security services for AI platforms Deploy and maintain AI/ML services such as Amazon SageMaker and Azure Machine Learning Support data scientists and ML engineers with optimized environments for model training and deployment Implement Infrastructure as Code ...

deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering ...

Degree in a relevant technical field Tech Environment Python, Java Cloud platforms AWS Containerisation and infrastructure-as-code tools Relational and non-relational databases Amazon Bedrock, Sagemaker, Vertex AI Datadog, Databricks, MLFlow, Grafana, OTel Claude, Gemini, ChatGPT, open-weight LLM models Terraform, Docker, K8s RMDBs, Graph DBs, Vector ...

selection, and performance trade-offs Ability to assess use case viability and business value Cloud & Technology Experience across at least two of: AWS (Bedrock, SageMaker) Azure (Azure ML, Azure OpenAI) GCP (Vertex AI) OpenAI ecosystem Plus: Understanding of data engineering and big data concepts Awareness of cloud security, scalability ...

hands-on or architectural experience with modern data platform tooling, including but not limited to Apache Airflow, dbt, Kafka, AWS Glue, AWS Redshift, AWS Sagemaker, AWS Dynamo, AWS Quick Sight. Success leading a data engineering team through complex challenges that are large in scope. Strong knowledge of modern data ...

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 ...