Responsibilities
- Improve content understanding and knowledge for GenAI-powered advertising
- Leverage state-of-the-art multimodal LLMs and agentic models to extract, structure, and retrieve valuable signals that power ad creative generation and optimization
- Pioneer the use of Reinforcement Learning from Human Feedback (RLHF) to post-train LLMs for real-world advertising performance
- Develop RL post-training frameworks that use actual ads data to fine-tune LLMs to generate ad creatives that resonate with users
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Has obtained a PhD in Computer Science, AI/ML, or a relevant technical field
- 2+ years of experience in NLP or multimodal LLM research and development
- Hands-on experience LLM post-training and/or reinforcement learning (reward modeling, PPO/GRPO, RLHF)
- Strong experience with ML tech stack (e.g., PyTorch, building data pipeline)
- Experience leading major technical initiatives with cross-functional impact, and/or influencing strategy across multiple teams
- Demonstrated significant industry influence in the field of AI and/or recently published research in leading peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV)
Preferred Qualifications
- Ability to bridge modeling and production - turning novel research ideas into shipped products
- First-author publications at top peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV)
- Background in ads systems
- Experience with recommendation systems or ranking models
$184,000/year to $257,000/year + bonus + equity + benefits
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