About the job
Global E-Commerce Content Recommendation team plays a central role in the company, driving critical product decisions and platform growth. The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact. The team is fast-pacing, collaborative and impact-driven.
Responsibilities
- Design algorithms and systems that leverage LLMs and generative models for content-to-commerce matching, product summarization, etc
- Explore novel architectures and strategies for generative recommendation systems
- Contribute to the research community via internal papers, patents, or external publications
- Drive scientific rigor while balancing real-world constraints
Qualifications
Minimum
- Individuals who are completing or have recently completed a PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
- Experience with LLMs (e.g., GPT, LLaMA, PaLM) or diffusion/generative models, through research or practical application
- Proficient coding skills in Python and hands-on experience with deep learning frameworks such as TensorFlow or PyTorch
- Demonstrated ability to conduct rigorous research and analyze large-scale data
- Strong problem-solving skills and a high sense of ownership
Preferred
- Publications in ML/AI conferences (e.g., NeurIPS, ICML, ACL, SIGIR, KDD, CVPR, RecSys)
- Experience with recommendation systems, retrieval models, or multi-modal learning
- Familiarity with building and deploying real-time, scalable ML systems in production
- Background in e-commerce or related applied AI research domains