Machine Learning Scientist Intern (Global E-Commerce Content Recommendation) - 2026 Summer (PhD)

What you'll do

• Build and improve recommendation systems and end-to-end machine-learning solutions for product challenges.
• Explore generative recommendation techniques and unified recommendations across livestreams, short videos, and search.
• Optimize recommendation algorithms and infrastructure, collaborating with cross-functional teams on product strategies.

What they ask for

• Currently pursuing a PhD in computer science, machine learning, or a similar field.
• Knowledge of theoretical and empirical research methods for addressing research problems.
• Experience with at least one popular deep learning framework and familiarity with deep neural network architectures.

Nice to have

• Research experience in applied machine learning, machine-learning infrastructure, large-scale recommendation systems, or market-facing machine-learning products.
• First-author publications at top AI conferences or journals; proficiency in C/C++, Python, and shell programming; or internship experience in an AI research organization.

Tools

Diffusion Models, PyTorch, TensorFlow, C/C++, Python

AI focus

Explore generative recommendation, including diffusion models, prompt learning, and multimodal content generation; build and optimize machine-learning recommendation systems.