Machine Learning Engineer

• Attract, retain, develop, manage, coach and assess ML Ops Engineers
• Lead engineers on implementation of the full ML lifecycle, including building and scaling ETL pipelines, deploying Data Scientist-developed models into customer-facing applications, and enabling organizational throughput through cloud infrastructure and tooling
• Own the roadmap for Machine Learning Engineering and Data Science tools, including developing reusable frameworks and standardized solutions to streamline model implementation
• Research, prototype and instruct the team on creating cutting-edge machine learning infrastructure
• Enable change for the team by moving decisions forward and eliminating blockers
• Provide technical thought leadership for Data Science managers on cloud-based tools and infrastructure for the ML lifecycle
• Instill best practices and foster a culture of continuous learning and development through training, coaching, pair programming and code review
• Contribute to development, monitoring, alerting, and automated testing frameworks to ensure reliability, performance, and integrity of data pipelines, models, and infrastructure
• Document and communicate implementations and best practices to leaders across Kohl’s broader data organization
• Stay current with Google Cloud Platform services and evolving MLE and ML Ops best practices
• Perform additional assigned tasks

Explore Manager, Machine Learning Operations at Kohl's. Review requirements and application details.