Position Type Career area Machine Learning Location 3485 SW Knowlton Rd, Beaverton, Oregon 97005, United States Job ID R-95900 Become a Part of the NIKE, Inc. Team 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. Lead Machine Learning Engineer– NIKE USA Inc., Beaverton, OR. Develop robust advanced analytics and machine learning solutions that have a direct impact on the business; own projects end-to-end - from conception to operationalization, demonstrating an understanding of the full software development lifecycle; provide technical vision and guidance to the teammates; work with the Artificial Intelligence and Machine Learning (Al/ML) team at Nike with teammates in Portland, Boston, and Poland, and join a global organization working to solve machine learning problems at scale; design and implement scalable applications that leverage prediction models and optimization programs to deliver data driven decisions that result in immense business impact; contribute to core advanced analytics and machine learning platforms and tools to enable both prediction and optimization model development; develop and share new skills, mentor, and contribute knowledge and software back to the analytics and engineering communities both within Nike and at-large. Telecommuting is available from anywhere in the U.S., except from SD, VT, and WV. Must have a Master’s degree in Information Systems, Computer Science and 2 years of experience in the job offered or in a engineering-related occupation. Position requires Python AWS (Amazon Web Services) Machine Learning / MLOps

• Docker
• CI/CD (Jenkins)

SQL and ETL Pipelines Data Structures, Data Modeling and Software Architecture

• Apache Spark
• Kubernetes

Databricks Terraform Database Technologies (Snowflake, PostgreSQL) Apply at www.jobs.nike.com (Job# R-95900) We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form. NIKE, Inc. is a growth company that looks for team members to grow with it. Nike offers a generous total rewards package, casual work environment, a diverse and inclusive culture, and an electric atmosphere for professional development. No matter the location, or the role, every Nike employee shares one galvanizing mission: To bring inspiration and innovation to every athlete* in the world. NIKE, Inc. is an equal opportunity employer. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability. What You Can Expect OUR HIRING GAME PLAN 01 Apply Our teams are made up of diverse skillsets, knowledge bases, inputs, ideas and backgrounds. We want you to find your fit – review job descriptions, departments and teams to discover the role for you. 02 Meet a Recruiter or Take an Assessment If selected for a corporate role, a recruiter will reach out to start your interview process and be your main contact throughout the process. For retail roles, you’ll complete an interactive assessment that includes a chat and quizzes and takes about 10-20 minutes to complete. No matter the role, we want to learn about you – the whole you – so don’t shy away from how you approach world-class service and what makes you unique. 03 Interview Go into this stage confident by doing your research, understanding what we are looking for and being prepared for questions that are set up to learn more about you, and your background.