ML Engineering Manager

About the Role

The role’s primary focus is to lead a team of engineers at all levels to operationalize data science models and solutions. You will ensure that data science initiatives are transformed into scalable, production‑ready systems and develop engineering solutions that enhance data‑driven capabilities across the organization. You will lead, mentor, and manage a collaborative, innovative engineering team, overseeing performance evaluations and supporting professional development to maintain high productivity and morale. Your leadership will foster a culture of continuous learning and teamwork. The manager will direct the deployment of data science models into production environments, guaranteeing scalability, reliability, and efficiency. This includes converting prototype models into production‑ready solutions and implementing best practices for continuous integration and continuous deployment (CI/CD). Engineering solutions will be designed and developed in close partnership with data scientists to translate models into robust, scalable systems and build infrastructure that strengthens the organization’s data‑driven capabilities. Technical guidance on software engineering and machine learning practices will ensure code quality, maintainability, and adherence to industry standards. Staying updated on emerging technologies and methodologies, you will incorporate best practices into the team’s workflows. You will work closely with data science, IT, and product teams to align engineering efforts with organizational goals and communicate complex technical concepts to non‑technical stakeholders. The manager will oversee computing resources, cloud services, and infrastructure needed for machine learning operations, optimizing resource utilization and cost efficiency while ensuring the team has the necessary tools and environments to perform effectively. Resource planning will include managing cloud platforms such as Azure and AWS and monitoring model performance in production. • Lead and mentor a team of engineers, overseeing performance evaluations and professional development. • Deploy and scale data science models using CI/CD pipelines and cloud infrastructure. • Design engineering solutions that convert prototypes into production‑ready systems. • Collaborate with data scientists, IT, and product teams to align engineering work with business goals. • Manage computing resources, cloud services (Azure, AWS), and ensure cost‑effective operations. • Join a collaborative environment within a company serving 200,000 customers across 500+ branches.

Key Responsibilities

• ▸team leadership
• ▸model deployment
• ▸ci/cd
• ▸cloud management
• ▸production design
• ▸resource optimization

What You Bring

Candidates typically need a BS/BA in a related discipline and at least 7 years of relevant experience; a certification or advanced degree can offset less experience. Preferred qualifications include three years of managerial experience overseeing engineering or software teams, expertise in Python, big‑data technologies (Hadoop, Spark, Databricks), cloud platforms (Azure, AWS), and a proven record of delivering scalable, sustainable engineering solutions. • Require 7+ years of relevant experience and at least 3 years in engineering leadership. • Demonstrated expertise in Python, Hadoop, Spark, Databricks, and cloud platforms. • BS/BA required; advanced degree in Computer Science or related field preferred.

Requirements

• ▸python
• ▸hadoop
• ▸spark
• ▸databricks
• ▸cloud
• ▸leadership

Benefits

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 by being deeply knowledgeable, fully capable, and always dependable, with associates driving this commitment. The position is based in a comfortable indoor environment with mostly sedentary work and occasional light lifting; travel is limited to less than 10% overnight trips. It is a hybrid role located in Doraville, GA. • Hybrid work location in Doraville, GA with occasional travel (<10% of the time).

Work Environment

Office Full-Time