Machine Learning Engineer Graduate (E-Commerce Recommendation Live) - 2027 Start (PhD)

What you'll do

• Build and optimize models for recall, pre-ranking, ranking, and mixed ranking.
• Develop cross-domain and multimodal modeling solutions for live commerce recommendations.
• Advance recommendation technologies and partner with teams to launch scalable solutions and measure impact.

What they ask for

• Completing or recently completed a PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related discipline.
• Strong machine learning foundation and expertise in at least one of recommendation systems, search, advertising, NLP, multimodal learning, or large-scale applied AI.
• Strong programming skills in Python or C++, with hands-on experience using deep learning frameworks such as PyTorch.
• Understanding of data structures, algorithms, and large-scale model training or production machine learning systems.

Nice to have

• Experience with recommendation systems, especially for live commerce, e-commerce, search, ads, or large-scale consumer products.
• Experience with generative recommendation, large recommendation models, LLMs or multimodal foundation models, or related modeling areas.

Tools

Python, C++, PyTorch

AI focus

Generative recommendation, large recommendation models, multimodal learning, reinforcement learning, and long-term value optimization for live commerce recommendations.