What are the responsibilities and job description for the ML Engineering Manager position at White Cap Supply Holdings, LLC?
A position at White Cap isn't your ordinary job. You'll work in an exciting and diverse environment, meet interesting people, and have a variety of career opportunities.
The White Cap family is committed to Building Trust on Every Job. We do this by being deeply knowledgeable, fully capable, and always dependable, and our associates are the driving force behind this commitment.
Job Summary
Responsible for leading a team of engineers at all levels, to operationalize data science models and solutions. Ensures that data science initiatives are effectively transformed into scalable, production-ready systems, and to develop engineering solutions that support and enhance data-driven capabilities across the organization.
Major Tasks, Responsibilities and Key Accountabilities
- Leads, mentors, and manages a team of engineers, fostering a collaborative and innovative environment. Oversee performance evaluations and support the professional development of team members to ensure high productivity and morale.
- Responsible for leading the deployment of data science models into production environments, ensuring scalability, reliability, and efficiency. The manager oversees the transformation of prototype models into production-ready solutions, implementing best practices for continuous integration and continuous deployment (CI / CD).
- Designs and develops engineering solutions that support data science initiatives. Collaborates closely with data scientists to translate models into robust, scalable systems and build infrastructure that enhances the organization's data-driven capabilities.
- Provides technical guidance on software engineering and machine learning practices, the manager ensures code quality, maintainability, and adherence to industry standards. Stay updated on emerging technologies and methodologies to incorporate best practices into the team's workflows.
- Works closely with data science, IT, and product teams to align engineering efforts with organizational goals. Communicates complex technical concepts to non-technical stakeholders, facilitating collaboration across departments to drive project success.
- Manages computing resources, cloud services, and infrastructure necessary for machine learning operations, optimizes resource utilization and cost efficiency. Ensures the team has the necessary tools and environments to perform effectively.
Nature and Scope
Work Environment
Education and Experience
Preferred Qualifications
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