DICK'S Sporting Goods
EngineeringManager,MachineLearning
Neural analysis suggests this role is
optimal for Manager candidates.
“Engineering Manager, Machine Learning at DICK'S Sporting Goods. Skills: Machine Learning, Agentic solutions, Inventory optimization. Lead ML solutions development. Deploy ML solutions”
What You'll Achieve.
Optimize inventory; Maximize assortment plans; Ensure product availability; Improve inventory effectiveness; Improve assortment effectiveness
Industry & Context.
Root cause analysis
Cameras must be on, AI tools not permitted, Satisfactory background check, ID verification
What They're Looking For.
Must Have
Bachelor's degree or equivalent experience, 6+ years experience machine learning, 2-3 years technical leadership, 1-3 years people management, Experience with ML frameworks, Python skills, Experience with Spark, Experience with Kafka, Experience designing ML APIs, Experience operating ML production systems, Experience working in Agile environment
Nice to Have
Master's degree preferred, Retail technology experience, Merchandising experience, Inventory planning experience
What You'll Do.
Lead ML solutions development
Maintain ML solutions
Define technical strategy
Guide ML architecture
Translate goals to solutions
Drive ML solutions delivery
Lead transformation initiatives
Deliver agentic solutions
Improve inventory effectiveness
Improve assortment effectiveness
Champion agile methodologies
Champion engineering best practices
Ensure quality standards
Ensure scalability standards
Ensure reliability standards
Ensure performance standards
Ensure security standards
Design cloud ML deployment
Design model lifecycle management
Align technical execution
Stay current with technologies
Recommend strategic improvements
Support portfolio management
Support performance management
Support information security
Foster diverse team environment
Foster inclusive team environment
Foster collaborative team environment
Lead systems-level design
Lead systems integration
Lead event stream integration
Lead vendor integrations
How You'll Work.
Team & Collaboration
Product Management; Design; Architecture; Business leaders; Engineering leaders
Process & Methodology
Agile methodologies
Full Job Description
At **DICK’S Sporting Goods** , we believe in how positively sports can change lives. On our team, everyone plays a critical role in creating confidence and excitement by personally equipping all athletes to achieve their dreams. We are committed to creating an inclusive and diverse workforce, reflecting the communities we serve. If you are ready to make a difference as part of the world’s greatest sports team, apply to join our team today! **OVERVIEW:** Join us as we transform technology, data, and analytics to build next-generation tools and platforms for athletes and teammates. As the Machine Learning Engineering Manager - Teamate, you will lead a highly skilled team, driving enterprise impact and shaping the future of a leading sports retailer. You will be at the forefront of merchandising improvement—delivering advanced machine learning and agentic solutions that optimize inventory, maximize assortment plans, and ensure the right products are available at the right time and place. You will collaborate closely with Product Management, Design and Architecture to ensure cross-functional alignment and deliver innovative software, while overseeing team development, talent management, and best practices to drive impactful results. Key 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 standard
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