Overview Join Global E-commerce's Data-E-commerce team to advance foundational multimodal models and agent-based systems for e-commerce. You will collaborate with top product and engineering peers to tackle long-term forecasting, cross-modal understanding, and intelligent decision-making at scale. You will shape a modular framework unifying users, products, content, and logistics, with practical impact on GMV growth and user retention. This role offers deep technical challenges and opportunities to publish, patent, and influence real-world shopping experiences.
Responsibilities- Design algorithms and systems that combine LLMs and generative models for content-to-commerce matching and product summarization
- Explore architectures for generative recommendation systems and end-to-end modeling with large models
- Contribute to internal papers, patents, or external publications to advance research
- Maintain scientific rigor while balancing real-world constraints in a production-like environment
Key requirements- PhD in a relevant technical discipline (software development, CS, or computer engineering)
- Strong foundation in machine learning with exposure to cutting-edge AI tech; publications or competition experience preferred
- Familiarity with Hadoop, MapReduce, and Spark
- Experience with TensorFlow or PyTorch for model training and deployment; knowledge of mixed precision and distributed training
- strong collaboration
- research-minded
- problem-solving
- LLMs and generative models
- multimodal modeling (CV/NLP)
- big data frameworks: Hadoop, MapReduce, Spark
