ML Engineering Manager

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

• Solutions require analysis and investigation.
• Achieves planned results by decisions and actions based on professional methods, business principles, and practical experience.
• Manages a group or team of professional individual contributors and/or indirectly supervises support staff.

Work Environment

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.
• Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.
• Typically requires overnight travel less than 10% of the time.

Education and Experience

• Typically requires BS/BA in a related discipline. Generally 7+ years of experience in a related field. May require certification. Advanced degree may offset less experience in some disciplines.

Preferred Qualifications

• 3 years' experience in a managerial or leadership role overseeing engineering or software-based teams.
• Proven track record of successfully delivering engineering and production solutions that are scalable and sustainable.
• Expertise in Python.
• Knowledge of big data technologies and platforms like Hadoop, Spark, and Databricks.
• Experience in managing complex projects involving cloud infrastructure, CI/CD, and model monitoring.
• Strong background in collaborating with cross-functional teams and effectively communicating complex technical concepts to non-technical stakeholders.
• Staying current with industry trends and emerging technologies in machine learning is expected to ensure the team remains at the forefront of innovation.
• Proficiency in cloud infrastructure, deployment pipelines, and software engineering.
• Proficiency in cloud platforms such as Microsoft Azure and Amazon Web Services (AWS).
• Advanced degree in Computer Science, or related field preferred.
• This is a hybrid role based in Doraville, GA.

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