Research Scientist Intern (Monetization Technology - Business Integrity) - 2027 Summer

What you'll do

• Build an end-to-end moderation system that automates rejection decisions, provides interpretable reasoning, and supports intelligent remediation.
• Develop moderation capabilities intended to handle evolving rules, complex content, scarce samples, adversarial behavior, and multiple languages.

What they ask for

• Currently pursuing a master's degree in a listed or related technical discipline, completed or expected within 12 months; exceptional bachelor's candidates with strong research output may also be considered.
• Research experience in Ads, Search, Recommender Systems, NLP, CV, Multimodal, or Agent technologies, demonstrated through publications, thesis work, internships, or research projects.
• Understanding of LLM pre-training, post-training/alignment, and evaluation, and ability to read, reproduce, and critique recent literature.
• Proficient in Python and at least one deep learning framework; able to independently formulate research problems and design controlled experiments.

Nice to have

• Publications at top-tier venues or equivalent evidence of research ability.
• Experience with RLHF/post-training, reasoning, model architecture design, evaluation benchmarks, LLM/VLM-as-Judge, agentic systems, RAG, multimodal applications, or production research.

Tools

Python, PyTorch, TensorFlow, RLHF, RAG

AI focus

Research and develop LLM-based moderation capabilities, including model training and alignment, evaluation, interpretability, adversarial-content handling, and automated moderation.