Large Recommendation Model Algorithm Engineer - Global E-Commerce

ByteDance
Singapore
Workplace: OnsiteFull timeFunction: Software EngineeringSkills: ["Self-driven","Original exploration","Research thinking","Engineering excellence","Hypothesis-driven validation"]

Build and optimize cross-scenario shared foundation models for e-commerce recommendation, advancing an event-sequence-driven generative paradigm. Apply LLM and multimodal technologies across retrieval, ranking, and re-ranking, contributing to model training and inference optimization. Research end-to-end generative recommendation and system optimization methods that balance efficiency and user experience, including integrating LLMs/VLMs to create adaptive intelligent recommenders.

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FursaFursa
ByteDance
ByteDance
1 month ago

Large Recommendation Model Algorithm Engineer - Global E-Commerce

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Source: Company careers pageValidated by: Fursa AI
Last checked: 30 days agoStatus: Live
Reposted: similar role first listed 1 month ago

Job Summary

Build and optimize cross-scenario shared foundation models for e-commerce recommendation, advancing an event-sequence-driven generative paradigm. Apply LLM and multimodal technologies across retrieval, ranking, and re-ranking, contributing to model training and inference optimization. Research end-to-end generative recommendation and system optimization methods that balance efficiency and user experience, including integrating LLMs/VLMs to create adaptive intelligent recommenders.
Location: Singapore
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering

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; participate in training and inference optimization.
  • •Explore integrating LLMs/VLMs with recommendation systems to develop adaptive and evolving recommenders.
  • •Research end-to-end generative recommendation and system optimization methods balancing efficiency and user experience.

Key Requirements

  • •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 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.
Experience:Large-scale recommendationLarge-model trainingLLMsMultimodal learningReinforcement learning
Skills:Self-drivenOriginal explorationResearch thinkingEngineering excellenceHypothesis-driven validation
Tech Stack:PythonPyTorchLLMsVLMsMultimodal understandingReinforcement learningFoundation models

Company Brief

ByteDance
Develops consumer internet and content platforms, including TikTok and other apps for short-form video, news, and entertainment. It also builds advertising, commerce, and creator tools that connect audiences, brands, and publishers across global markets.
Industry: Digital Media
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Established Company
Headquarters: Beijing, China
Founded: 2012
WebsiteLinkedIn