14 of 14 Amazon SageMaker Jobs in the South West

APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge of data privacy, accessibility ...

APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge of data privacy, accessibility ...

APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge of data privacy, accessibility ...

APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge of data privacy, accessibility ...

APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge of data privacy, accessibility ...

APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge of data privacy, accessibility ...

have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live systems Experience with MLOps tools (MLflow, Weights & Biases, DVC, or similar) Hands-on exposure to LLM/GenAI ...

Computer Science, Machine Learning, Engineering , or a closely related discipline. Bonus Points Experience with MLOps and model serving platforms such as BentoML, MLflow, or SageMaker . Hands-on work with streaming and batch data pipelines using tools like Spark, Airflow, or Apache Beam . Background in front ...

designing, supporting, and operating ML systems in production Technical environment (experience expected across most of these) MLflow (expert-level) Databricks Cloud platforms (AWS preferred; SageMaker exposure a bonus) CI/CD for ML workloads Docker and Kubernetes Infrastructure as Code (Terraform or similar) Python-based ML workflows ...

designing, supporting, and operating ML systems in production Technical environment (experience expected across most of these) MLflow (expert-level) Databricks Cloud platforms (AWS preferred; SageMaker exposure a bonus) CI/CD for ML workloads Docker and Kubernetes Infrastructure as Code (Terraform or similar) Python-based ML workflows ...

designing, supporting, and operating ML systems in production Technical environment (experience expected across most of these) MLflow (expert-level) Databricks Cloud platforms (AWS preferred; SageMaker exposure a bonus) CI/CD for ML workloads Docker and Kubernetes Infrastructure as Code (Terraform or similar) Python-based ML workflows ...

designing, supporting, and operating ML systems in production Technical environment (experience expected across most of these) MLflow (expert-level) Databricks Cloud platforms (AWS preferred; SageMaker exposure a bonus) CI/CD for ML workloads Docker and Kubernetes Infrastructure as Code (Terraform or similar) Python-based ML workflows ...

designing, supporting, and operating ML systems in production Technical environment (experience expected across most of these) MLflow (expert-level) Databricks Cloud platforms (AWS preferred; SageMaker exposure a bonus) CI/CD for ML workloads Docker and Kubernetes Infrastructure as Code (Terraform or similar) Python-based ML workflows ...

designing, supporting, and operating ML systems in production Technical environment (experience expected across most of these) MLflow (expert-level) Databricks Cloud platforms (AWS preferred; SageMaker exposure a bonus) CI/CD for ML workloads Docker and Kubernetes Infrastructure as Code (Terraform or similar) Python-based ML workflows ...