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AI Texture Synthesis Quality Engineer

Adrian Bergmann

Full-time · Job · Los_Angeles

About the role

Generated 3D assets look impressive in a demo reel but fall apart in production when you zoom in on the textures. Tiling artifacts, color banding, resolution inconsistencies, and material property mismatches are the enemies — and our clients' artists catch every one. Our texture synthesis pipeline generates PBR-ready materials (albedo, normal, roughness, metallic) from text descriptions, and your job is making sure they're production-quality. You'll build the quality assurance layer: automated metrics that detect tiling seams, perceptual similarity models that compare generated textures against artist-created references, and A/B testing infrastructure that measures which improvements users actually prefer. The target is reducing artist rejection rates from 30% to under 10%. The visual AI team is seven engineers. You'll sit between the generation team (who build the synthesis models) and the product team (who hear from angry artists). Your quality metrics become the gate between "model improvement" and "production release."

Responsibilities

  • Build automated quality metrics for generated PBR texture materials
  • Develop perceptual similarity models comparing generated vs artist-created textures
  • Design A/B testing infrastructure for texture quality preferences
  • Detect and flag tiling artifacts, color banding, and resolution issues
  • Create the quality gate between model updates and production releases
  • Track quality trends across model versions and texture categories

Requirements

  • 3+ years in computer vision or graphics with texture or material experience
  • Understanding of PBR materials: albedo, normal maps, roughness, metallic
  • Strong PyTorch skills for perceptual model development
  • Experience with image quality metrics and perceptual evaluation
  • Interest in 3D graphics and digital content creation workflows

Benefits

  • Fully remote with flexible hours
  • Health and dental insurance
  • $3,000 annual equipment budget
  • Access to high-end GPU cluster
  • Work with cutting-edge generative AI

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

AI & Machine Learning Engineers MLOps & AI Infrastructure

Skills

python pytorch computer vision docker gcp mlflow

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