Beaverton, Oregon, United States of America
23 hours ago
Machine Learning Engineer

Machine Learning Engineer – Nike USA Inc.- Beaverton, OR. Develop robust advanced analytics and machine learning solutions that have a direct impact on the Supply Chain infrastructure; own projects end-to-end - from conception to operationalization, demonstrating an understanding of the full software development lifecycle; provide technical vision and guidance to your teammates; work with the Artificial Intelligence and Machine Learning (AI/ML) team; work 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; and work closely with the global team, along with commercial and consumer analytics, and enterprise architecture teams. Telecommuting is available from anywhere in the U.S., except from SD, VT, and WV 

Must have a Master’s degree in Computer Science and Engineering, Machine Learning, Data Science, Computer Information Systems, and 2 years of experience in the job offered or an Engineering-related occupation. Experience must include: 

 

Agile Software Development 

ETL 

Git 

Docker 

REST API 

Python 

AWS 

Pandas 

Machine Learning 

 

 

Apply at www.Nike.com/Careers (Job# R-70336)  

#LI-DNI

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.

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