Job Description

Are looking for an opportunity to jumpstart your career in hightech? Do you see yourself as an energetic, curious and driven professional who wants to join a fast-growing, award-winning visual AI startup, Syte is looking for you. Syte is the leading AI-driven visual search and recommendation technology for retail.

Syte is looking for a self-motivated, organized and detail orientated Tagging Specialist

What you’ll do:

Review, classify and tag hundreds of images (fashion, accessories etc)
You will be working on labelling, tagging and entering data into large data systems to train the algorithm, responsible for the visual search tool
Execute tasks in a timely manner and to a high degree of quality

Benefits

company swag; relaxed dress code; snacks

Qualifications

Required skills:
Posses the ability and patience to stay focused on repetitive tasks for long periods of time without compromising on quality
A methodical approach to tasks with attention to detail
Patience and an eye for small details
High level of English (reading, speaking and writing)
Good communication and interpersonal skills and the ability to work as part of a team
Strong time management and load balancing skills
Problem-solving skills with the ability to think “out-of-the box”
Ability to work independently.

*Please send CV’s in English*

Company Description

Syte is pioneering the future of eCommerce discovery, using AI-driven visual search and recommendation technology for retail. We are on a mission to make shopping delightful, seamless, and intuitive by empowering brands to instantly connect shoppers with products they love. We partner with top brands, like Farfetch, PrettyLittleThing, Conforama, Shane Co., and Zozo, to provide on-demand, hyper-personalized experiences that drive conversion, increase average order value, and spark lifelong loyalty. Our visual discovery and personalization technology platform that helps retailers and ecommerce to increase revenue by using state-of-the-art deep learning algorithms personalizing each customer interaction.
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