Backend Engineer - Large Model Knowledge System/Content understanding/RAG (ByteDance Singapore)
Tasks
- Build multimodal content understanding pipeline
- Deliver domain knowledge base solutions for public cloud products
- Design and optimize large model RAG and knowledge base architecture
- Drive cloud native monitoring billing and elastic scheduling iteration
- Implement large scale vector retrieval
- Implement video representation models
- Maintain and extend backend architecture of in house vector databases
- Optimize model inference performance
- Optimize vector computing components
- Resolve service availability throughput and storage bottlenecks
- Support multimodal unstructured data processing and storage
Perks/Benefits
- N/A
Skills/Tech-stack
Cloud Native | Cloud-native monitoring | Elastic Scheduling | Inference Optimization | Knowledge Base | Knowledge-base architecture | Model Inference | Model Inference Optimization | Multimodal Learning | Performance Tuning | Retrieval-Augmented Generation | Storage Optimization | Vector Database | Vector Retrieval | Vector computing | Video Representation
Education
N/A
Roles
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