Role Overview
We are seeking a versatile Data Scientist to lead the development of high-quality, audio-driven digital avatars. This role combines cutting-edge Generative AI with foundational Machine Learning to create responsive, identity-consistent virtual humans. You will bridge the gap between "brain" and "body" by integrating RAG-based agents with multimodal synthesis models (ViT/VLM) to build avatars that don't just look real—they interact intelligently.
Core Responsibilities
Multimodal Synthesis: Develop SOTA audio-to-video pipelines using Vision Transformers (ViT) and VLMs to drive lip-sync, micro-expressions, and head poses.
Intelligent Interaction: Architect RAG (Retrieval-Augmented Generation) systems using LangChain and AI Agents to provide avatars with a searchable knowledge base and autonomous reasoning capabilities.
Customized Avatar Generation: Build person-specific fine-tuning workflows ( LoRA , Adapters ) to ensure 1:1 identity preservation from minimal reference footage.
Hybrid Modeling: Apply a mix of Deep Learning (CNNs for texture, RNN/LSTM for temporal audio sequences) and Classical ML (XGBoost/Random Forest for metadata classification or signal gating).
End-to-End Optimization: Own the pipeline from raw audio/text input to real-time rendered output, ensuring low-latency performance on GPU clusters.
Required Technical Stack
Qualifications
Experience: 5+ years in Data Science with a focus on Multimodal ML or Digital Humans.
Education: Master’s or PhD in CS, AI, or a related quantitative field.
Problem Solving: Proven ability to solve the "uncanny valley" through superior temporal consistency and identity-aware fine-tuning.
Location:
Guangzhou (DTC)
Job:
Analytics
Schedule:
Regular
Employee Status:
Full time
