LoRA Fine-Tuning Engineer (Video Motion Optimization)
We are running a technical project focused on improving motion realism in AI-generated videos using LoRA fine-tuning. The base model produces unnatural movement and weak prompt compliance. The goal is to train posture-specific LoRA models that significantly improve motion quality using carefully curated short video datasets.
This project is strictly focused on motion optimization through fine-tuning (not content creation).
Scope of Work
* Prepare and curate short training videos following strict technical rules
* Trim, split, and clean videos (remove black frames, mixed actions, wrong shots)
* Re-encode videos to required format (resolution, fps, aspect ratio, duration)
* Build JSONL dataset lists and upload data to object storage
* Configure LoRA fine-tuning tasks for video generation models
* Select and tune training parameters (rank, alpha, batch size, epochs, learning rate)
* Train posture-specific LoRA models (one posture per model)
* Run inference tests and compare base model vs fine-tuned results
* Iterate on data quality and training strategy to improve results
* Provide documentation of training settings and workflow
Project-based.
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