Principal Machine Learning Engineer

Ll Oefentherapie; Olympia (WA); On-site; USD 120,000 - 180,000; Full time

Job summary

Ll Oefentherapie is seeking a machine learning engineer to scale and productionize models within our systems. You will build robust ML pipelines, monitor model performance, and automate workflows to ensure reliable deployment across environments.

You will collaborate with stakeholders to integrate models into existing platforms, diagnose issues, and maintain internal tooling. Staying current with ML developments will help you continuously improve modeling outcomes.

Responsibilities

• 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.

Job description

• 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.