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

What you'll do

• Build and optimize models across recall, pre-ranking, ranking, and mixed ranking.
• Develop cross-domain and multimodal models for live-commerce recommendations.
• Work with cross-functional teams to launch scalable solutions, run experiments, and measure impact.

What they ask for

• Completing or recently completed a bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related discipline.
• Solid machine-learning foundation and experience in at least one of recommendation systems, search, advertising, NLP, multimodal learning, or large-scale applied AI.
• Strong Python or C++ programming skills and hands-on experience with 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 in live commerce, e-commerce, search, ads, or large-scale consumer products.
• Experience with generative recommendation, large recommendation models, LLMs, multimodal foundation models, or related modeling and optimization areas.

Tools

Python, C++, PyTorch, LLMs

AI focus

Develop recommendation models and technologies, including generative recommendation, large recommendation models, reinforcement learning, multimodal representation learning, and long-term value optimization.