AI/Computer Vision Engineer Animation & VFX Pipelines

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Georgia IT

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Job Position(s): AI/Computer Vision Engineer Animation & VFX Pipelines
Project Type: Various Projects
Job Date: Full Time
Compensation: Paid - Salary
Union Status: Non-Union

 

Job Title: AI/Computer Vision Engineer Animation & VFX Pipelines

Location: Remote
Experience Level: 5+ Years
Employment Type: Full-time / Contract (Flexible)

Job Summary

We are seeking a highly skilled AI/Computer Vision Engineer with strong expertise in animation, VFX, or digital art pipelines to help design and scale AI-powered image description and multimodal search systems. The ideal candidate will combine experience in computer vision, image recognition, vector databases, and scalable deployments with knowledge of creative industry tools (Maya, Katana, etc.).

This role is highly cross-functional, involving image-to-text, text-to-image, and image-to-image search systems, integration with models/APIs, and support for next-generation creative workflows.

Key Responsibilities

  • Design and scale AI-driven image description and search pipelines.
  • Implement multimodal search systems (text-to-image, image-to-image).
  • Integrate with computer vision and image recognition APIs.
  • Develop scalable deployments using vector databases for large media datasets.
  • Collaborate with creative tech teams (animation, VFX, digital art) to ensure alignment with pipeline workflows.
  • Contribute to model training, fine-tuning, and optimization for performance.
  • Maintain documentation and best practices for reproducibility and scalability.

Required Skills

  • 5+ years of experience in AI/Computer Vision.
  • Strong knowledge of digital media classification, search, and retrieval.
  • Familiarity with animation/VFX pipelines and tools such as Maya, Katana, Nuke, Houdini, or similar.
  • Experience with Python, ML frameworks (TensorFlow, PyTorch).
  • Proficiency in vector databases (e.g., Pinecone, Milvus, Weaviate) for scalable search.
  • Hands-on experience with model deployment at scale (cloud or on-premise).

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