AI Research Scientist - Monetization, GenAI

MGenAI is focused on making significant progress in AI-powered content generation for ads applications. In the past two years, generative AI has seen some of the most significant breakthroughs ever achieved, particularly in large language models and generative image models. Meta Monetization GenAI’s mission is to lead the charge in applied generative AI technology and build products that will help businesses become more productive and efficient. The London team is particularly focused on image and video ad creative generation.

Individuals in this role are expected to be recognized experts in AI and machine learning, particularly in areas such as generative AI and computer vision. The ideal candidate will have a keen interest in producing new applied science to make computers more intelligent, and more importantly convert that into production at a large scale.AI Research Scientist - Monetization, GenAI Responsibilities

• Lead applied research to advance the science and technology of image/video/text generation for applications in ad creative generation and editing
• Work towards long-term ambitious research goals, while identifying intermediate milestones
• Lead efforts in productionization of GenAI technologies in ads domain applications
• Influence progress of relevant research communities by producing publications

Minimum Qualifications

• Has a Ph.D. or is in the process of obtaining a PhD degree in computer vision or machine learning
• At least one publication as the first author, and at least 3 as co-authors on the following six venues: NeurIPS, CVPR, ICML, ICLR, ICCV, and ECCV
• At least 3 years of experience in generative AI research
• Experience in leading a team of applied research scientists and engineers in solving real world ML problems in industry, in a role with primary emphasis on AI research.
• Experience in developing and debugging in Python

Preferred Qualifications

• Experience in developing diffusion models for image/video/text/multimodal generation with publications on this topic on NeurIPS, CVPR, ICML, ICLR, ICCV, or ECCV
• Experience in developing real-world applications using multimodal Large language Models

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