SENIOR MANAGER AI/ML ENGINEERING

Nike - Beaverton, OR

Full-time - Senior

Beaverton, OR

Leather and Allied Product Manufacturing

About the position

As a Senior Manager in AI/ML Engineering at NIKE, Inc., you will lead and grow teams of machine learning engineers, data scientists, and software architects to deliver scalable AI and machine learning solutions. This role involves working at the intersection of machine learning and engineering (MLOps) to provide innovative services that enhance Nike's supply chain. You will advocate for engineering best practices and the adoption of new technologies, while coaching engineers to elevate their skills and careers.

Responsibilities

• Lead and grow teams of machine learning engineers, data scientists, and software architects.
• Deliver scalable machine learning and AI solutions to customers across the business.
• Engage employees and assist teams by removing roadblocks to drive progress.
• Develop and drive innovative solutions that delight customers.
• Stay current with industry trends and recommend relevant technologies in analytics and machine learning.
• Model clarity and accountability as a leader, building trust and strong relationships.
• Mentor teams and individuals to foster high-performing teams and contributors.
• Set high standards for engineering excellence and drive innovation.

Requirements

• Bachelor's Degree in computer science, software engineering, or applicable field (Ph.D. preferred).
• 7+ years of experience in developing production-grade software in software or data engineering, machine learning, or related fields.
• 4+ years in a leadership or management role using Agile frameworks.
• Familiarity with ETL, ML, or analytics technologies such as Scikit-learn, Dask, Tensorflow, Kubeflow, Spark, EMR, or similar platforms.
• Strong communication skills to articulate technical topics and connect them to business value.
• Experience with open-source technologies and making build/buy decisions in Data Science, AI, & ML.
• Deep knowledge of software architecture and engineering best practices for deploying machine learning at scale.
• Experience in team leadership and building relationships across Product, Architecture, and Engineering.

Nice-to-haves

• Experience delivering analytics and ML products.
• Knowledge of modern cloud computing stacks for deploying machine learning.

Benefits

• Generous total rewards package
• Casual work environment
• Diverse and inclusive culture
• Professional development opportunities