Research Scientist, Google Ads

• Author research papers to share and generate impact of research results across the team and in the research community. 
  
• Help in growing research business across teams by sharing research trends and best practices within the community. 
  
• Develop novel machine learning and large language modeling techniques that influence Google products.
• Post-train and finetune Large Language Models (LLMs) for large-scale retrieval, pseudo-rater, and other Google Ads applications.
• Collaborate closely with researchers across Google and DeepMind.

Minimum qualifications:

• PhD in Computer Science, a related field, or equivalent practical experience.
• Experience working on modern large language model post-training (e.g., supervised fine-tuning, RLHF) or core generative model development in an industry AI lab, research institute, or frontier AI organization.
• One of more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred qualifications:

• 3 years of experience working in frontier AI research labs on pre-training or post-training teams.
  
• 1 year of experience owning and initiating research agendas.
• 1 year of experience with generative AI concepts (e.g., LLMs, diffusion) and development workflows.
• Experience in large language models or other generative AI tuning and optimization techniques.
• First author publications in top machine learning conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, COLM).

• PhD in Computer Science, a related field, or equivalent practical experience.
• Experience working on modern large language model post-training (e.g., supervised fine-tuning, RLHF) or core generative model development in an industry AI lab, research institute, or frontier AI organization.
• One of more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).