Meta AI Researcher Ruiyu Li Shares Career Insights

Ruiyu Li, a research scientist at Meta, explains how her academic background and internships led her to a successful career in AI.

Ruiyu Li, a 26-year-old AI research scientist at Meta, believes that her research publications played a crucial role in landing her role at the tech giant. Based in Menlo Park, Li specializes in artificial intelligence and machine learning, focusing on training AI models for advanced recommendation systems and optimizing large language models (LLMs).

Graduating from college in 2022 and completing her Master’s in machine learning from Carnegie Mellon University in 2023, Li navigated a challenging tech job market. Career fairs and conferences did not yield fruitful connections, yet she managed to receive three offers from major tech firms. Initially joining Microsoft, she eventually chose to work at Meta.

Li emphasized the importance of foundational knowledge in algorithms and coding to excel in the AI field. While AI technologies assist greatly in efficiency, she insisted that having solid technical skills remains indispensable. “If you want to work in AI, you need to be familiar with algorithms and coding,” she stated.

Her advice for aspiring candidates centers on acquiring hands-on experience with AI technologies, either through internships at startups or by publishing research papers. During her college years, she interned at a startup where she was directly involved in innovative applications of AI, offering her valuable insights.

“When I look at candidates, I check if they have research and projects. During competitive job markets, it’s not enough to simply list experience or projects on your résumé,” Li explained. She believes that published papers or open-source contributions significantly enhance a candidate’s appeal to employers.

Before her tenure at Meta, she was engaged in academic research at eight different AI labs, where she honed her skills in numerous machine learning areas. At Meta, Li has leveraged her academic foundation to contribute to production AI systems, ensuring that model quality aligns with scalability and reliability.

The practical experience gained through her internships, she noted, became invaluable in preparing her for the full-time position. During these internships, she worked on generative search algorithms and delivered critical projects that integrated AI into video generation pipelines.

Li’s specialization in large-scale AI systems and AI video generation not only helped her stand out among peers but also provided her a robust set of transferable skills beneficial in her present role. She encourages those interested in AI to pursue graduate education to deepen their understanding and improve their career prospects.