Computer Vision Specialist Engineer – Garment & Human Segmentation (Deep Learning, PyTorch)
Budget: €5,000 – €10,000 EUR
Project Overview
We’re building next-generation AI tools for the fashion industry and need a Computer Vision Specialist Engineer to develop precise garment and human segmentation models. Your work will power core features in our apps, delivering seamless digital try-ons, outfit analysis, and interactive experiences.
Key Responsibilities
Architect, train and deploy deep learning models for semantic & instance segmentation of garments and people
Create custom networks tuned for clothing attributes (e.g. fabric type, cut, drape) and human body parts under varied poses and lighting
Optimize models for low-latency, high-accuracy inference in production (mobile/web)
Lead data pipeline: collect images/videos, define annotation strategy, preprocess inputs, validate labels
Integrate vision modules with backend services and front-end clients in collaboration with product, design, and engineering teams
Produce clear technical documentation and present model results to stakeholders
Required Skills & Experience
Master’s in CS, EE, Applied Math, or related field
2+ years building and shipping computer vision solutions
Expert in segmentation architectures (Mask R-CNN, U-Net, DeepLab) with demonstrable projects on garments or fine-grained part recognition
Strong Python proficiency and hands-on experience with PyTorch or TensorFlow
Solid command of OpenCV and classic vision methods (edge detection, morphological ops)
Track record of tuning models for speed and resource constraints
Bonus Qualifications
Open-source contributions or publications in CV conferences (CVPR, ICCV, ECCV)
Familiarity with ComfyUI for UI-driven model workflows
What We Offer
Work on AI innovations reshaping online fashion
Collaborative team culture, flexible hours
Competitive compensation and benefits
Clear path for career growth and learning
We’re building next-generation AI tools for the fashion industry and need a Computer Vision Specialist Engineer to develop precise garment and human segmentation models. Your work will power core features in our apps, delivering seamless digital try-ons, outfit analysis, and interactive experiences.
Key Responsibilities
Architect, train and deploy deep learning models for semantic & instance segmentation of garments and people
Create custom networks tuned for clothing attributes (e.g. fabric type, cut, drape) and human body parts under varied poses and lighting
Optimize models for low-latency, high-accuracy inference in production (mobile/web)
Lead data pipeline: collect images/videos, define annotation strategy, preprocess inputs, validate labels
Integrate vision modules with backend services and front-end clients in collaboration with product, design, and engineering teams
Produce clear technical documentation and present model results to stakeholders
Required Skills & Experience
Master’s in CS, EE, Applied Math, or related field
2+ years building and shipping computer vision solutions
Expert in segmentation architectures (Mask R-CNN, U-Net, DeepLab) with demonstrable projects on garments or fine-grained part recognition
Strong Python proficiency and hands-on experience with PyTorch or TensorFlow
Solid command of OpenCV and classic vision methods (edge detection, morphological ops)
Track record of tuning models for speed and resource constraints
Bonus Qualifications
Open-source contributions or publications in CV conferences (CVPR, ICCV, ECCV)
Familiarity with ComfyUI for UI-driven model workflows
What We Offer
Work on AI innovations reshaping online fashion
Collaborative team culture, flexible hours
Competitive compensation and benefits
Clear path for career growth and learning