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Meta is seeking AI research scientists to help us build the solutions for Personalization of Meta AI. We're looking for researchers with LLM post training LLM expertise to join us on working with improving the personalization of LLM responses. Our team contributes to post training recipe, evaluations and tool calling for personalizing MetaAI’s responses. We are tackling complex challenges from synthetic data curation, developing reinforcement learning environments and recipes, user profiling at Meta’s scale and frontier paradigms that redefine what is possible.
Job Responsibility:
Collaborate with cross-functional teams to develop and improve personalization in Meta’s frontier foundation models
Directly contribute to experiments, including designing experimental details, authoring reusable code, running evaluations, and organizing results
Prioritize research that can be applied to Meta's product development
Lead complex research projects end-to-end
Requirements:
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Phd in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Experience in Generative AI models and building LLM technologies particularly post training
Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward. Proven experience of proactively identifying, scoping and implementing innovative research solutions
Programming experience in Python and hands-on experience with frameworks like Pytorch, Spark
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Nice to have:
Hands on experience in Personalization with LLMs particularly on designing agentic systems, RAG and Reinforcement learning based post training techniques
First author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL)