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

TikTok
Singapore
Workplace: OnsiteInternshipFunction: Healthcare (Clinical, Medical, Wellness)Education: bachelorsSkills: ["Research mindset","Self-driven","Passion","Hypothesis-driven learning"]

Join the E-commerce Recommendation Foundation team to build unified foundation models for multi-scenario recommendation, spanning retrieval, ranking, and re-ranking. Work on an event-sequence-driven generative recommendation paradigm integrating LLMs, multimodal understanding, reinforcement learning, and system optimization. Contribute to model training and inference optimization, explore LLM/VLM integration for adaptive recommenders, and research end-to-end generative recommendation methods balancing efficiency and user experience.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
TikTok
TikTok
1 day ago

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

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 12 hours agoStatus: Live

Job Summary

Join the E-commerce Recommendation Foundation team to build unified foundation models for multi-scenario recommendation, spanning retrieval, ranking, and re-ranking. Work on an event-sequence-driven generative recommendation paradigm integrating LLMs, multimodal understanding, reinforcement learning, and system optimization. Contribute to model training and inference optimization, explore LLM/VLM integration for adaptive recommenders, and research end-to-end generative recommendation methods balancing efficiency and user experience.
Location: Singapore
Workplace: Onsite
Employment Type: Internship
Job Function: Healthcare (Clinical, Medical, Wellness)
Seniority: Intern level

Key Responsibilities

  • •Build and optimize cross-scenario shared foundation models for unified modeling and efficient inference.
  • •Advance an event-sequence-driven generative recommendation paradigm integrating multimodal understanding and generative capabilities.
  • •Apply LLM technologies across retrieval, ranking, and re-ranking, including model training and inference optimization.
  • •Explore integration of LLMs/VLMs with recommendation systems to create adaptive, evolving recommenders.
  • •Research end-to-end generative recommendation and system optimization methods balancing efficiency and user experience.

Key Requirements

  • •Currently pursuing an Undergraduate or Master's 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.
  • •Experience or publications in LLMs, multimodal learning, reinforcement learning, or generative recommendation (preferred).
Experience:Recommendation systemsMachine learningDeep learningLLMsMultimodal learningReinforcement learning
Education:Bachelor's in Software Development, Computer Science, Computer Engineering, or related technical discipline
Skills:Research mindsetSelf-drivenPassionHypothesis-driven learning
Tech Stack:PythonPyTorchLLMsVLMsMultimodal understandingReinforcement learningFoundation models

Company Brief

TikTok
Short-form video platform that lets users create, share, and discover entertainment content through algorithmic recommendations. It also offers advertising and creator tools for brands, influencers, and businesses.
Industry: Digital Media
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Headquarters: Singapore, Singapore
Founded: 2016
WebsiteLinkedIn