MACHINE LEARNING ENGINEER - SUPPLY CHAIN

Nike - Beaverton, OR

Full-time - Entry Level

Remote - Beaverton, OR

Leather and Allied Product Manufacturing

About the position

As a Machine Learning Engineer at NIKE, Inc., you will develop advanced analytics and machine learning solutions that significantly impact the Supply Chain infrastructure. This role requires a strong background in algorithms, data structures, and hands-on experience with AWS and database technologies. You will own projects from conception to operationalization, providing technical vision and guidance to your team while working in an agile product model.

Responsibilities

• Develop robust advanced analytics and machine learning solutions for the Supply Chain infrastructure.
• Design and implement scalable applications leveraging prediction models and optimization programs.
• Contribute to core advanced analytics and machine learning platforms and tools.
• Provide technical vision and guidance to teammates.
• Work collaboratively with global teams and contribute to the analytics and engineering communities.

Requirements

• Bachelor's degree in Computer Science or relevant experience.
• 1-3 years of professional experience in software engineering, data engineering, or machine learning.
• Strong problem-solving and analytical mindset.
• Ability to write maintainable and extendable code in Python, containerized in Docker, and automated with CI/CD.
• Experience with agile development and test-driven development.
• Understanding of data structures, data modeling, and software architecture.
• Experience with data sets, ETL pipelines, SQL, and general data engineering.
• Exposure to MLOps, API development, or mathematical optimization is highly desirable.
• Experience with cloud architecture and technologies, particularly AWS.
• Familiarity with technologies like Spark, Kubernetes, Docker, Jenkins, Databricks, and Terraform.

Nice-to-haves

• Experience with MLOps, API development, or mathematical optimization.
• Familiarity with Spark, Kubernetes, Docker, Jenkins, Databricks, and Terraform.

Benefits

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