WHO YOU’LL WORK WITH
This internship is part of Nike’s Advanced Product Intelligence team, a group within the Advanced Innovation Collective, that focuses on building intelligent capabilities for designers, engineers, and creators to reimagine the future of physical product design. During your internship, you’ll work closely with multidisciplinary teammates across ML Engineering, Computational Engineering, Generative AI Design, and Data Analysis.
WHAT YOU’LL WORK ON
In the role of an AI/ML Engineer Intern, you will apply your AI/ML expertise to help teams explore, evaluate, and improve product concepts faster. You will build intelligent models, workflows, and prototypes that use product performance data to accelerate the product innovation process. You will lead or collaborate on efforts such as:
- Prototyping AI/ML tools that support engineering and creative workflows for footwear and apparel design and simulation
- Exploring applications of AI/ML and product performance data to engineering simulation workflows, including physics-based modeling, FEA, optimization, and virtual product development
- Training lightweight, domain-specific predictive ML models using generated, simulated, experimental, or curated datasets
- Building interactive prototypes or internal tools that make intelligent capabilities usable and understandable by Design and Engineering teammates
Over the course of the internship, you’ll work alongside a passionate and multidisciplinary team that’s shaping the future of product innovation at Nike. You’ll present your project to stakeholders at the end of the internship and contribute to documentation that helps scale your work beyond the summer. And finally, you’ll walk away with meaningful, real-world experience at the intersection of AI/ML and breakthrough products that make athletes* better.
WHO WE ARE LOOKING FOR
We’re looking for a graduate-level engineering intern with a strong foundation in machine learning and artificial intelligence who is eager to apply those skills to real-world challenges in product innovation. Candidates with experience in computational engineering, mechanical engineering, simulation, digital product development, or physics-based modeling are especially encouraged to apply.
This internship will be project-based, with room for tailoring based on your interests and strengths. Our ideal candidate brings not only technical capability, but also a self-directed, builder mindset and a curiosity for solving ambiguous and novel problems. You love digging into real-world datasets, training models, testing outputs—and improving them. You’re as excited by open-ended creative problems as you are by well-defined engineering challenges.
- Currently pursuing a Master’s degree in Computer Science, Machine Learning, Data Science, Computational Engineering, Mechanical Engineering, or a related technical field with a graduation date between Winter 2027 and Summer 2028
- Strong foundational understanding of core machine learning concepts (e.g., supervised & unsupervised learning, neural network architectures, model training and evaluation, tradeoffs in model selection, overfitting and underfitting behavior)
- Hands-on experience building AI/ML-powered systems, workflows, or technical prototypes (either academic, personal, or professional)
- Experience in one or more relevant areas, such as surrogate modeling, computer vision, transformers, 3D geometry, or simulation data
- Exposure to engineering simulation methods such as finite element analysis (FEA), computational modeling, optimization, or design exploration
- Proficiency in Python and commonly used ML libraries (e.g., PyTorch, OpenCV, NumPy, pandas, TensorFlow, scikit-learn)
- Comfort navigating ambiguous problem spaces and proposing your own ideas or approaches
- Demonstrated ability to communicate technical findings to diverse audiences in verbal and written form
This is a 10-week paid internship opportunity with relocation assistance. Curious to know what it’s like to be part of a world-class Internship Program? Check out our recap video from last summer: Nike Internship Program Recap Video
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.
Skills Required
- Currently pursuing a Master's degree in Computer Science, Machine Learning, Data Science, Computational Engineering, Mechanical Engineering, or a related technical field
- Graduation date between Winter 2027 and Summer 2028
- Strong foundational understanding of machine learning concepts, including supervised and unsupervised learning, neural networks, model training and evaluation, model selection, and overfitting
- Hands-on experience building AI/ML-powered systems, workflows, or technical prototypes
- Experience in one or more areas such as surrogate modeling, computer vision, transformers, 3D geometry, or simulation data
- Exposure to engineering simulation methods such as finite element analysis, computational modeling, optimization, or design exploration
- Proficiency in Python and commonly used machine learning libraries such as PyTorch, OpenCV, NumPy, pandas, TensorFlow, or scikit-learn
- Ability to navigate ambiguous problem spaces and propose ideas or approaches
- Demonstrated ability to communicate technical findings to diverse audiences verbally and in writing
Nike Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nike and has not been reviewed or approved by Nike.
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Retirement Support — A 401(k) with a company match is complemented by options such as a Mega Backdoor Roth and deferred compensation for eligible earners. Financial coaching and structured savings programs support long-term financial security.
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Equity Value & Accessibility — An Employee Stock Purchase Plan with a stock discount sits alongside broad-based equity vehicles like RSUs and non-qualified stock options. These avenues expand wealth-building opportunities beyond base pay.
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Parental & Family Support — Paid parental leave includes maternity and paternity time, recently expanded in the U.S. to 16 weeks and extended to part-time retail teammates. Additional supports include childcare assistance at select locations and family-building benefits such as fertility, surrogacy, and adoption.
Nike Insights
What We Do
At NIKE, Inc., we innovate to serve athletes*. Every teammate - from coder to creator - plays a role in making these athletes’ dreams real. Our tech, data, and digital teams push limits every day, building the future of sport and the tools that drive it. Here, curiosity is fuel. Innovation is the game plan. Different perspectives keep us on the offense. You’ll solve challenges worth tackling, grow fast and belong to a team that backs you to do the right thing. Bring your drive. Bring your bold. Let’s move the world, together. Take your first step at nike.com/careers * If you have a body, you’re an athlete.
Why Work With Us
At NIKE, Inc., your dedication fuels the future of sport. There is a sense of pride that comes from representing an iconic brand and shaping its future. Here, we treat every day as a new opportunity to push boundaries, ask tough questions and share whole-hearted convictions. We are a team – united by the belief that anything is possible.
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