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

TikTok

Singapore

On-site

SGD 140,000 - 210,000

Full time

14 days+

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Job summary

TikTok is building the next-generation recommendation intelligence within the E-commerce Recommendation Foundation team, focusing on unified models for multi-business scenarios and end-to-end generative capabilities. We pursue cross-disciplinary research and engineering excellence, inviting graduates with strong ML foundations to contribute to fast, impactful developments.

Successful candidates will work on MLOps-friendly model training, inference optimization, and integration of LLMs with

Qualifications

  • 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.

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.

Skills

Python
Machine Learning / DL
Self-driven research mindset
Strong problem-solving

Education

PhD in Computer Science/Software Engineering/EE, or related

Tools

PyTorch
LLM knowledge

Job description

Responsibilities

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.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

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 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.

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