Backend Engineer - Large Model Knowledge System/Content understanding/RAG (ByteDance Singapore)

About The Team:

The Volcano Engine Vector Database Knowledge Base team supports both internal and ToB customer requirements. We are responsible for the massive content processing of the Volcano Engine large model knowledge base and the effect tuning, evaluation and monitoring, and algorithm architecture optimization of the retrieval system architecture. We also provides technical solutions in framework construction, new feature delivery, and vertical solution construction.

Responsibilities:

1. Build and iterate the multimodal content understanding pipeline, resolve service availability, throughput, and storage bottlenecks to improve development efficiency.
2. Optimize vector computing components and model inference performance, and implement large-scale vector retrieval and video representation models for massive video content.
3. Design and optimize large model RAG and knowledge base architecture, and deliver general domain knowledge base solutions for public cloud products.
4. Maintain and extend the backend architecture of in-house vector databases to support multimodal unstructured data processing and storage.
5. Drive iteration of cloud-native capabilities including monitoring, billing, and elastic scheduling for vector database and knowledge base services.

Requirements:

Minimum Qualifications:

1. Bachelor’s degree in Computer Science or a related field.
2. 3+ years of professional software development experience in backend, AI infrastructure, or cloud services.
3. Solid programming skills in at least one of Python/C++/Golang/Java, with strong problem-solving abilities.
4. Basic understanding of large model applications and RAG systems, with passion for AI and cloud implementation.
5. Good communication and collaboration skills, proactive in tackling challenging problems.

Preferred Qualifications:

1. Experience in recommendation, search, advertising, recall or ranking systems.
2. Familiarity with Py Torch/Tensor Flow; experience in high-performance computing or CUDA.
3. Knowledge of high-concurrency, high-throughput system design; cloud or database experience.
4. Experience contributing to open-source projects.