Applied Computer Vision Engineer

Responsibilities

• Build and maintain preprocessing pipelines for virtual try-on, including segmentation, pose estimation, human parsing, and body mapping.
• Validate and standardize inputs so downstream models receive clean and consistent data.
• Benchmark and integrate new computer vision models and measure performance on internal evaluation datasets.
• Run dataset quality checks and resolve the failures they identify.
• Work with ML scientists to move research into production pipelines that run daily.
• Own reliable production computer vision pipelines used by brand partners.

Requirements

• Hands-on production experience in applied computer vision.
• Proficiency with Python and PyTorch.
• Experience with segmentation or pose estimation.
• A record of shipping production pipelines rather than working only in research.
• Comfort owning data quality and evaluation in a fast-moving startup environment.

Benefits

• San Francisco-based hybrid work arrangement.
• Significant ownership in a small team building production pipelines for brand partners.
• Opportunity to work on visible computer vision problems involving people, garments, and virtual try-on.