Nike logo

Data & Machine Learning Engineer Undergraduate Internship

Nike

Join the NIKE, Inc. Team

NIKE, Inc. is more than just a company that outfits the world's best athletes. It is a place where potential is explored, boundaries are obliterated, and the edges of what can be are pushed. We are looking for individuals who can grow, think, dream, and create. Our culture thrives on embracing diversity and rewarding imagination. At NIKE, Inc., it's about each person bringing their skills and passion to a challenging and constantly evolving game.

About the Role

NIKE is a technology company at its core. From our flagship website and five-star mobile apps to developing products, managing big data, and providing leading-edge engineering and systems support, our teams at NIKE Global Technology are revolutionizing the future at the confluence of tech and sport. We invest in and develop advances in technology, employing the most creative people in the world, and then give them the support to constantly innovate, iterate, and serve consumers more directly and personally.

Who We Are Looking For

The Artificial Intelligence and Machine Learning Group at NIKE applies machine learning to solve problems across the company. We develop fundamental technologies, conduct applied research and development, and deliver solutions to production to enable AI/ML across NIKE.

The ideal intern candidate is a leader with a demonstrated interest in developing complex data solutions and working on end-to-end solution design. You are a passionate data enthusiast who loves finding relationships between disparate data sets and clarity in a muddied data environment. You are continually learning and finding opportunities to share knowledge with others.

What You'll Experience

Our goal for the Data & Machine Learning Engineering Internship is to provide an incredible and unique experience, showing what it is like to be at NIKE full-time. As a Data Engineer, you will apply machine learning and engineering expertise to improve existing algorithms and understand and leverage core concepts of AI/ML to research and develop new algorithms. You will collaborate in multi-functional teams to support other groups working on science or science-engineering-related work.

Intern Project Examples Include:

  • Integrating Machine Learning within our technologies to identify and resolve incidents faster and more efficiently.
  • Scaling NIKE's innovation teams and our sustainability goal of moving to zero waste through the use of computer vision, code, agile methodologies, and robotics.
  • Ensuring people with disabilities have equitable access to NIKE's Technology using Artificial Intelligence.

What You Will Bring

Qualifications:

  • Enrolled in an undergraduate program in computer science, mathematics, statistics, or a related technical subject area with an expected graduation date between Winter 2025 or Spring/Summer 2026.
  • 0-2 years of work experience.
  • Resume submission (PDF) required.

Technical Skills:

  • Knowledge of Python, SQL, and Tableau.
  • Knowledge of AI/ML techniques such as neural networks, tree ensembles, regressions, etc.
  • Deep understanding of data structures and algorithms.
  • Deep understanding of solution and technical design.
  • Strong problem-solving, debugging, testing, and analytical skills.
  • Ability to quickly pick up new programming languages, technologies, and frameworks.

NIKE, Inc. is committed to employing a diverse workforce. 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.

Benefits

Whether it's transportation or financial health, we continually invest in our employees to help them achieve greatness - inside and outside of work. All who work here should be able to realize their full potential.

Benefits
Extracted with AI

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

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