Large Recommendation Model Algorithm Engineer- Global E-Commerce

TIKTOK PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

TikTok is expanding its E-commerce Recommendation Foundation team in Singapore, building next-generation foundation models for cross-scenario recommendations. You will work at the intersection of retrieval, ranking, and generation with large language models and multimodal understanding.

Join a research-forward engineering culture that values curiosity, experimentation, and impact, and contribute to systems that adapt to user needs with efficiency and scalability.

Qualifications

• Solid theoretical foundation in machine learning, deep learning, or information retrieval.
• Proficiency in Python and PyTorch or similar DL frameworks.
• Strong passion for intelligent recommendation systems and a self-driven research mindset.

Responsibilities

• Build and optimize cross-scenario shared Foundation Models for unified modeling.
• 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.

Skills

Python

Machine learning theory

Research mindset

Tools

PyTorch

Job description

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is 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 bring joy - a mission we work towards every day.

We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

TikTok 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 TikTok, our mission is to inspire creativity and bring joy. 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.

About the Team

The E-commerce Recommendation Foundation team is dedicated to building the next-generation recommendation intelligence. We aim to develop a unified Foundation Model that supports multi-business and multi-scenario recommendation systems, covering the full pipeline from retrieval and ranking to re-ranking, and driving a comprehensive upgrade in intelligence and generative capability.

We believe the future of recommendation systems goes beyond predicting click-through rates - it lies in understanding the relationship between people and content, and in generating new connections. The team is exploring an event-sequence-driven generative recommendation paradigm, deeply integrating large language models (LLMs), multimodal understanding, reinforcement learning, and system optimization to advance recommendation systems toward general-purpose intelligent agents.

We value original exploration and encourage both research thinking and engineering excellence. Every team member is empowered to propose hypotheses and validate ideas in an open environment - your code and papers may help define the next paradigm of recommendation systems. We seek individuals with a general intelligence mindset to join us in redefining the future of recommendation.

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.

Minimum 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.

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.