Principal Machine Learning Engineer

Oracle Corporation; Cheyenne (WY); Presencial; USD 120.000 - 160.000; Jornada completa

Descripción de la vacante

Oracle Corporation in Wyoming is seeking an experienced ML Engineer to help implement production-grade machine learning models and ensure their readiness for deployment. The role focuses on automating ML workflows, building robust infrastructure, and monitoring model performance in live environments.

You will collaborate with stakeholders to integrate models into existing systems, develop internal tools, and write clean, efficient code while staying current with advances in the ML field.

Responsabilidades

• Implements machine learning models for production.
• Ensures the readiness of machine learning models for deployment in production.
• Automates machine learning workflows.
• Creates infrastructure and frameworks to monitor the performance of machine learning models in deployment.
• Evaluates potential data quality, security, and/or privacy issues and their impacts on modeling.
• Provides troubleshooting and debugging support.
• Addresses issues in machine learning infrastructure and workflows.
• Collaborates with stakeholders to integrate machine learning models into new or extant systems.
• Develops, maintains, and refines tools, platforms, and services for internal use.
• Develops efficient, bug-free code from scratch.
• Maintains familiarity with current developments in the machine learning field and integrates knowledge into model development.

Descripción del empleo

• Implements machine learning (ML) models for production.
• Ensures the readiness of machine learning models for deployment in production.
• Automates machine learning workflows.
• Creates infrastructure and frameworks to monitor the performance of machine learning models in deployment.
• Evaluates potential data quality, security, and/or privacy issues and their impacts on modeling.
• Provides troubleshooting and debugging support.
• Addresses issues in machine learning infrastructure and workflows.
• Collaborates with stakeholders to integrate machine learning models into new or extant systems.
• Develops, maintains, and refines tools, platforms, and services for internal use.
• Develops efficient, bug-free code from scratch.
• Maintains familiarity with current developments in the machine learning field and integrates knowledge into model development.