Nike - Beaverton, OR

posted about 1 month ago

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
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