Large Recommendation Model Algorithm Engineer Graduate (Global E-Commerce) - 2027 Start (PhD)

ByteDance; Singapore; On-site; SGD 70,000 - 105,000; Full time

Job summary

ByteDance is seeking a Large Recommendation Model Algorithm Engineer Graduate (Global E-Commerce) for a 2027 start. The role focuses on building and optimizing foundation models, cross-scenario sharing, and exploring LLM/VLM integration within a scalable recommender system.

You will work with Python and PyTorch, contribute to research in large-scale models, and collaborate across teams to balance efficiency and user experience.

Qualifications

• PhD in CS/ML or related field.
• Strong foundations in machine learning/deep learning/information retrieval.
• Proficiency in Python and PyTorch.

Responsibilities

• Build and optimize cross-scenario shared Foundation Models for unified modeling and efficient inference.
• Advance event-sequence-driven generative recommendation, integrating multimodal understanding and generative capabilities.
• Apply LLM technologies across retrieval, ranking, and re-ranking; participate in training and inference optimization.

Skills

PhD in CS/ML

Python

PyTorch

Research mindset

Education

PhD

Tools

PyTorch

Job description

Large Recommendation Model Algorithm Engineer Graduate (Global E-Commerce) - 2027 Start (PhD)

Location:

Team:

Technology

Employment Type:

Regular

Job Code:

A85220A

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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.
• Research end-to-end generative recommendation and system optimization methods that balance efficiency and user experience.

Qualifications

Minimum Qualifications

• Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• 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.

Preferred Qualifications

• Experience in large-scale recommendation system development or large-model training, with notable technical achievements in a sub-area.
• Research experience or publications in LLMs, multimodal learning, reinforcement learning, or generative recommendation.
• Familiarity with pre-training and post-training processes for large language models (LLMs) or Foundation Models.

Job Information

About Us

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.

Why Join ByteDance

Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.

Diversity & Inclusion

ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.