Foundation Model Engineer - Global E-Commerce Recommendations

ByteDance; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

ByteDance is seeking researchers/engineers for the E-commerce Recommendation Foundation team. You will work on unified Foundation Models spanning retrieval to re-ranking, leveraging LLMs, multimodal signals, and reinforcement learning to advance intelligent recommendation systems.

The role emphasizes original exploration, open collaboration, and opportunities to influence the next paradigm of recommendation engines for ByteDance's global products.

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.
• Apply LLM technologies across retrieval, ranking, and re-ranking stages; participate in model training, inference optimization, and system co-design.
• Explore integration of LLMs/VLMs with recommendation systems to develop adaptive intelligent recommenders.
• Research end-to-end generative recommendation and system optimization methods that balance efficiency and user experience.

Skills

Machine Learning

Deep Learning

Information Retrieval

Python

Research mindset

Tools

PyTorch

LLMs

Foundation Models

Job description

ByteDance is seeking researchers/engineers for the E-commerce Recommendation Foundation team. You will work on unified Foundation Models spanning retrieval to re-ranking, leveraging LLMs, multimodal signals, and reinforcement learning to advance intelligent recommendation systems.

The role emphasizes original exploration, open collaboration, and opportunities to influence the next paradigm of recommendation engines for ByteDance's global products.