Machine Learning Engineer Intern (E-Commerce Recommendation Video)- 2027 Summer

What you'll do

• Scale recommendation models and optimize their training and production serving under strict latency constraints.
• Develop generative retrieval using semantic item representations and large models, and apply model knowledge to user-interest discovery.
• Optimize recommendation training and inference, build agent-assisted R&D workflows, and research recommendation problems such as retention and cold start.

What they ask for

• Currently pursuing an undergraduate degree in Software Development, Computer Science, Computer Engineering, or a related discipline.
• Strong machine-learning and engineering fundamentals, including algorithms, data structures, and clean, efficient, reproducible code.
• Deep research or engineering practice in at least one area: LLMs/foundation models, NLP, CV, RL, or recommendation/search/ads.
• Enthusiasm for applying LLM/LRM techniques in production and ability to define and decompose ambiguous problems.

Nice to have

• Publications at listed venues or comparable venues, or high-quality open-source work.
• Experience in areas such as CUDA/Triton, distributed training, LLM post-training, agent systems, inference acceleration, or recommendation/search/ads projects.

Tools

LLMs, RQ-VAE, SID, CUDA, Triton, SFT, RLHF, DPO

AI focus

Build and scale LLM-based recommendation and generative retrieval; use large and reasoning models for user-interest discovery; develop agent-assisted R&D workflows; and conduct original research on recommendation.