NEWROPE's core technology is image recognition specialized in fashion. We provide fashion companies with two types of applications installed with the AI as SaaS.
Huge amounts of clothes are disposed each year. 13 million tons of clothing and textile waste in just the United States alone. This averages out to be roughly 200 T-shirts per person. This problem pollutes the environment. Additionally, it is also a reason that brands, retailers and other fashion companies face difficulties in business.
Supply chains and trends in the industry are really complicated. On the other hand, there are various kinds of data such as sales results, items posted on SNS, user’s action histories online, coordinates and so on. As you know, dealing with big data is AI’s strong area. That’s why we believe we are able to contribute to the industry.
By reducing dead stock and optimizing matching of end-users and items, we can enable our customers to make profit. The profit could be resources to create next brands, designs, customer experiences and culture.
Recommendation engines for fashion E-commerce
Our artificial intelligence recommends items like shop staff. “Image search” supports end-users to find similar items to what they are searching, and “AI stylist” suggests styling, how to coordinate items.
Our AI has recognized fashion snapshots in SNS such as Instagram and Twitter, and collected trend data since 2017. Our customers are able to know what is in fashion and optimize their merchandising, marketing, pricing and so on based on the actual data.
What you’ll be doing:
・ Responsible to develop functionalities that utilize our AI systems
・ Responsible to deliver functionalities based on our business needs and performance targets
・ Join our agile workflow as an in-house software engineer (not as an AI researcher nor a data scientist)
・ At the beginning, start from development of one specific product, but gradually join developments of other products while learning necessary technologies
・ Keep improving product quality through testing and peer code review
Build, test, and manage interactions between multiple systems
What we need to see:
・ Over three years of experience as a software engineer
・ Skill set required to start development on at least one product; For more details of our technologies, see below.
・ Understandings of key concepts of information security and ability to build a system that can avoid security threats
・ Ability to competently use modern standard architecture and guide others in doing so
・ Open to cooperation with other departments
・ Ability to break down a rough architecture design into a detailed one
・ Open mind on feedback from users to dig real needs
・ Basic skills about technologies that we use for developing most of our products: Docker, Basic operation skills on Linux, RDB/SQL, REST API
Nice to have:
・ Japanese language skill
・ Experience in low-layer technologies that can be useful for operating our systems
・ High technical skills we don’t have and can be applied to our system
5,000,000 yen – 8,000,000 yen per year
(Based on your career and skill level.)
・ Travel expenses will be paid
・ Pay revision: 2 times per year
・ Probation period is 6 months, with no difference in salary.
・ Newrope is a startup focusing on the fashion industry.
・ Flexible team consists of 4 engineers including 3 foreigners, a data scientist, 2 editors, 2 sales, and CEO.
・ Working in Shibuya which is a source of fashion in Japan.
・ Have self-developed AI systems: Can work in the frontier of technologies.
・ Data-centric systems: We work for users. But also, we think gathering data for AI systems is essential. So, we need to work on invisible systems from users, and keep thinking “what is good data?”. This is challenging work.
・ Work in Tokyo, communicate in English: If you like Japan but are not good at Japanese, Newrope should be an excellent company to work.
・ Flexible working style: Only outcomes are required. Our corporate culture actively accepts new stuff to improve our productivity. If you join us, we’ll trust you as long as you drive our project.