Live opening · Posted 17 hours ago

Textile Specialist Intern

Fynd · Mumbai, Maharashtra, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 17 hours ago
CompanyFynd
LocationMumbai, Maharashtra, India (On-site)
Work modeNo
SourceLinkedin
ListedPosted 17 hours ago

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About the role

Description supplied by the original job listing.

Location: Mumbai, Maharashtra (On-site) Role: Textile Microscopy & Data Intern
About Us We are building next-generation digital fabric creation and material scanning technology. We are developing proprietary computer vision and AI pipelines to automate complex textile analysis
The Role We are looking for a detail-oriented intern with a background in textiles to spearhead our physical data collection and do R&D.
You will be managing the physical bridge between the raw yarn and the digital camera rig. Your primary mission will be executing precision sample preparation based on AATCC standards or our automated scanning pipeline.
What You Will Do
Prepare high-volume, high-density fiber samples from various yarn spools (Cotton, Linen, and blends).
Perform liquid-mount dispersions (using water/glycerin slurries and capillary wicking) to create completely flat, non-overlapping glass slides.
Operate our digital microscopy rig to scan and capture clear longitudinal images of the dispersed fibers.
Log, organize, and manage the resulting image datasets for the machine learning team.
What We Are Looking For
Background: Currently pursuing or recently completed a degree/diploma in Textile Technology, Textile Engineering, or Material Science.
Lab Skills: Extremely steady hands and the patience required for high-volume microscopic sample preparation.
Microscopy Knowledge: Familiarity with operating optical microscopes. You should understand depth of field, focal planes, and basic slide preparation.
Knowledge of Fibers: You know the structural difference between the twist of a cotton fiber and the nodes of a flax fiber.
Tech-Adjacent: You don’t need to know how to code, but an interest in how physical textile testing intersects with AI and computer vision is a huge plus.

Work arrangement
No

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