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Specialized VFX+ML skillset reduces applicants, but mid-level ML demand and metro location keep competition medium.
Core ML/CV skills are transferable, but VFX-specific pipelines and EXR workflows increase domain sensitivity.
Strong mandatory ML/CV tooling and VFX pipeline skills required, but no explicit years filter.
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Develop, deploy, and optimize machine learning models specifically for VFX production tasks such as object detection, segmentation, motion tracking, and image/video enhancement.
Build AI-powered tools for asset tagging, script/metadata extraction, and quality control analysis, integrating these ML solutions into VFX production pipelines like Nuke and Unreal.
Design and maintain scalable inference pipelines while collaborating with VFX artists and pipeline teams to embed ML into real-time or near real-time production workflows.
Proficient in Python programming.
Experience with ML/DL frameworks such as PyTorch and TensorFlow.
Strong understanding of Computer Vision and Deep Learning architectures including CNNs and Transformers.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in integrating machine learning models into production VFX pipelines and tools (e.g., Nuke, Unreal).
Skilled in handling large multimedia datasets and image/video processing workflows, preferably with knowledge of EXR and color pipelines.
Capable of designing scalable ML inference systems optimized for real-time or near real-time VFX production environments.