Fashion Tech Marketing Intern, 5 Hours Per Week, Fall-Winter-Spring 2026/2027

Summer-Fall-Winter 2026/2027 Marketing Intern

Eye BeamIt (EB; Belmont, CA) is a stealth, early-stage startup which has developed an advanced patent-pending mobile commerce platform for fashion brands allowing consumers to get real-time information about and, most importantly, buy apparel and accessories that they see on someone else. It is Shazam for fashion.[1]

EB’s combination of app and server software, IoT (Internet of Things) hardware, and machine learning algorithms will finally allow brands to capitalize immediately on the consumer’s impulse to buy when he or she first becomes interested. In addition, EB will store all the data it gathers in a scalable, high performance-database and provide analysis to the brands, thereby capitalizing on the treasure trove of valuable demographic and real-time data. 

New data shows the challenges computer vision apps based on conventional AI have with this task. Two of these apps – Google Lens Style Match and ScreenShop, for which Kim Kardashian served as advisor, were found to identify the exact same item in zero [0] out of 935 attempts.[2] There may be physics challenges for such software-only solutions on smartphones. One source stated that these phones have already reached the limit of the number of pixels they can reasonably put in their camera chips. It describes diffraction issues that a 2012 Nokia phone with 41 megapixels had and notes that 12 to 16-megapixel sensors are likely to be standard for the foreseeable future.[3] Also, while there is debate, an understanding of the limitations of today’s conventional AI is becoming clearer.[4]   A Google Research Scientist (and now Director of Machine Learning at Apple) stated “most arbitrary points in space are misclassified. For example, one network we tested classified roughly 70% of random noise samples as being horses, with high confidence.”[5] An Assistant Professor of Computational Biology at Caltech says “GPT-3, the largest deep learning language model, produces text nearly indistinguishable from that written by a human. But it requires 10 trillion sentences to learn, its training cost is over $10 million, and the training process consumes 190,000 KWh, the amount needed to drive a car 435,000 miles.”[6] Since 100 billion new apparel items are produced annually[7], the training set for this problem may be 225X to 1,000,000X too large for conventional AI to handle. A Machine Learning Professor at Caltech says elephants in the room for AI include training set size and quality of training data. Generative AI obtains training data from the internet. Self-driving cars should not use Generative AI because the internet is not a good source of training data.[8] Similarly, EB believes Generative AI may not be appropriate to address the Shazam for fashion problem because photo shoot images of apparel and accessory items on models from the internet may differ significantly from images of actual items being worn inside and outside. EB, like Amazon Go stores, uses a combination of software and hardware to provide a highly reliable solution.

The company has one patent pending in Europe and one granted in the US, each with multiple claims, for its technology, and possesses additional trade secret knowledge. EB is actively exploring collaboration with an assistant professor of computational biology at a leading research university and his team with the goal of incorporating next-generation, bio-inspired, self-training AI algorithms into EB's platform. This could lead to EB having early access to this technology.

The company projects annual revenue to be $200 million five years after closing its first venture round. Eye BeamIt’s total addressable market opportunity by 2022 is estimated at $12 Billion per year with the potential to be larger over time.

Fall-Winter-Spring 2026/2027 Marketing Internship Description:

Organize women’s focus groups to:

• Test EB software platform, including app and database, for performance at reasonable scale, usability, and enthusiasm generated.
• Obtain suggestions on new features or improvements to current capabilities.

Persuade/ help to persuade general managers of premium or luxury fashion brands to partner with EB to put on events / parties at their stores or outside of their stores.

Other marketing tasks as needed or as proposed by the intern.

Contribute to cross-functional product team leading to successful store fashion party when bandwidth available. 

Required Qualifications:

• Undergrad working toward BA, BBA or similar degree, recent BBA or MBA graduate or similar degree, or equivalent.
• Experience, ability, and/or interest in marketing to fashion or luxury brands or consumers.
• Solid communication, planning, and organizational skills.
• Ability and interest in working with product team.

Desired Qualifications:

• Experience with, knowledge of, or interest in fashion or luxury retail, merchandising, or other positions in  fashion or luxury brands.

Additional Position Information:

• This is for Fall-Winter-Spring 2026/2027.
• Some meetings will be remote. Organizing women’s focus groups and persuading premium or luxury fashion brands to partner with EB on store or outside store events will be in-person.

Contact: 

Jim Simmons

CEO, Eye BeamIt

https://www.linkedin.com/in/JamesPSimmonsJr/

http://www.eyebeamit.shop

email: jpsimmonsjr@gmail.com

[1] Wall Street Journal, 4-30-19 (https://www.wsj.com/articles/does-a-shazam-like-app-for-clothing-exist-11556640029 )

[2] Data taken by Jim Simmons, CEO, Eye BeamIt; and Ariel Hasse, BS, Physics, Caltech, and Advisor to Eye BeamIt ( https://www.linkedin.com/in/ariel-hasse-67752974/ ).

[3] “Why haven’t we seen another 41- megapixel smartphone camera?,” Android Authority, 11-13-17 (https://www.androidauthority.com/super-high-resolution-smartphone-cameras-807829/ )

[4] The Economist, 6-11-20 (https://www.economist.com/technology-quarterly/2020/06/11/an-understanding-of-ais-limitations-is-starting-to-sink-in )

[5] “Deep Learning Adversarial Examples – Clarifying Misconceptions,” Ian Goodfellow, Research Scientist, Google, KDnuggets Post, July, 2015 ( https://www.kdnuggets.com/2015/07/deep-learning-adversarial-examples-misconceptions.html )

[6] Personal communication, January, 2021.

[7] Sources: McKinsey, 10-20-16 (https://www.mckinsey.com/business-functions/sustainability/our-insights/style-thats-sustainable-a-new-fast-fashion-formula# ) states that "The number of garments produced annually has doubled since 2000 and exceeded 100 billion for the first time in 2014." World Economic Forum (WEC), 4-22-16 (https://www.weforum.org/agenda/2016/04/our-love-of-cheap-clothing-has-a-hidden-cost-it-s-time-the-fashion-industry-changed/ ) states "Consumers have never had so much clothing and at such dirt cheap prices. To be more precise, we have purchased 100% more items of clothing this year than we did just 30 years ago and we wear those pieces on average only seven times before getting rid of them. Globally that adds up to an astonishing 150 billion new clothing items made annually." Footwear, bags, luggage, and other accessories are not included in these estimates.

[8] Personal conversation with Machine Learning Professor, Caltech, 8-10-23.