Engineering Manager, Machine Learning

DICK'S Sporting Goods is a leading sports retailer committed to creating an inclusive and diverse workforce. As the Machine Learning Engineering Manager, you will lead a skilled team to drive enterprise impact through advanced machine learning solutions that optimize inventory and merchandising effectiveness.

Responsibilities:

• Lead the development, deployment, and maintenance of scalable, reliable machine learning solutions for merchandising and inventory optimization
• Define and guide technical strategy and architecture for enterprise-grade ML, and AI capabilities
• Manage, mentor, and develop a high-performing team of machine learning engineers
• Partner with product, business, and engineering leaders to translate goals into ML-driven solutions
• Drive end-to-end delivery of ML solutions from discovery through production support
• Lead transformation initiatives delivering ML and agentic solutions that improve inventory and assortment effectiveness
• Champion agile methodologies and engineering best practices
• Ensure high standards for quality, scalability, reliability, performance, and security
• Design cloud-based ML deployment patterns including APIs, monitoring, and model lifecycle management
• Align technical execution with business priorities and KPIs
• Stay current with emerging technologies and recommend strategic improvements
• Support portfolio management, budgeting, performance management, and information security
• Foster a diverse, inclusive, and collaborative team environment
• Lead systems-level design and integration, including APIs, event streams, and vendor-managed integrations
• Plan and manage resources and lead onshore/offshore contractors

Requirements:

• Bachelor's degree or equivalent experience in a quantitative field
• 6+ years of experience in machine learning or related engineering fields
• 2–3 years of experience in a technical leadership role
• 1–3 years of people management experience
• Experience with ML frameworks
• Strong Python skills and experience with distributed data technologies such as Spark and Kafka
• Experience designing and operating ML-powered APIs and production systems
• Experience working in an Agile environment
• Ability to influence senior and executive stakeholders
• Retail technology experience required
• Master's degree or equivalent experience in a quantitative field
• Merchandising or inventory planning experience