Sr Manager, AIML Engineering: NIKE, Inc.

NIKE, Inc. does more than outfit the world’s best athletes. It is a place to explore potential, obliterate boundaries and push out the edges of what can be. The company looks for people who can grow, think, dream and create. Its culture thrives by embracing diversity and rewarding imagination. The brand seeks achievers, leaders and visionaries. At NIKE, Inc. it’s about each person bringing skills and passion to a challenging and constantly evolving game.

About the Role:
We are looking for a seasoned Engineering leader to lead and grow teams of machine learning engineers, data scientists, and software architects. This role is focused on developing, implementing, and optimizing Gen AI solutions to transform the customer service experience. You will lead the Gen AI strategy for customer support, overseeing the entire lifecycle of AI agents and tools, from ideation and development to deployment and ongoing performance improvement. The work will accelerate Nike's core mission of serving athletes.

Responsibilities:

Inspire by building Proofs-of-Concept (POCs) and showing the art of the possible in AI.

Develop software architecture and platform strategy for Gen AI applications.

Recruit, hire, and mentor exceptional data scientists, machine learning engineers, and software engineers.

Work with product management, engineering, platform development, and other stakeholders to define requirements, guide product vision, and prioritize efforts.

Collaborate with a cross-functional agile team to build new product features.

Help drive optimization, testing, and tooling to improve data quality and iterate quickly on product quality through continuous A/B testing.

Ensure rigorous engineering processes are followed.

Requirements:

Bachelor’s Degree in computer science, software engineering, or a related field (Master’s or Ph.D. preferred).

8+ years of relevant work experience, including 4+ years of people management experience.

Must have launched an AI application at a global scale.

Deep technical understanding of the latest generative AI applications like large language models (LLMs), large multimodal models (LMMs), and image/video generation.

Proven success implementing and scaling Gen AI systems, with expertise in conversational AI technologies like RAG and cloud platforms (AWS, Azure, GCP).

Demonstrated experience in Machine Learning, AI, or distributed systems development (Java, Scala, Python, or similar).

Strong mathematical background in statistics and machine learning.

Excellent communication skills and ability to coordinate internally and externally.