Lead Large-Scale Recommendation Model Engineer

Bytedance; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

ByteDance Singapore is building the E-commerce Recommendation Foundation team to advance next-generation recommendation intelligence. The mission is to develop a unified Foundation Model supporting multi-business and multi-scenario pipelines, spanning retrieval, ranking, re-ranking, and generative capabilities.

Join a research-driven team that values hypothesis testing, code, and papers in shaping the future of recommendations.

Qualifications

• Solid theoretical foundation in machine learning, deep learning, or information retrieval.
• Proficiency in Python and familiarity with mainstream deep learning frameworks (e.g., PyTorch).
• Strong passion for intelligent recommendation systems and a self-driven research mindset.

Responsibilities

• Build and optimize cross-scenario shared Foundation Models to enable unified modeling and efficient inference.
• Advance the event-sequence-driven generative recommendation paradigm, integrating multimodal understanding and generative capabilities.
• Apply LLM technologies across retrieval, ranking, and re-ranking stages; participate in model training, inference optimization, and system co-design.
• Explore the integration of LLMs / VLMs with recommendation systems to develop adaptive and evolving intelligent recommenders.

Skills

Machine learning

Deep learning

Information retrieval

Tools

Python

PyTorch

Job description

ByteDance Singapore is building the E-commerce Recommendation Foundation team to advance next-generation recommendation intelligence. The mission is to develop a unified Foundation Model supporting multi-business and multi-scenario pipelines, spanning retrieval, ranking, re-ranking, and generative capabilities.

Join a research-driven team that values hypothesis testing, code, and papers in shaping the future of recommendations.