Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.
Meta is seeking Research Interns to join our Meta Superintelligence Lab in one of the post-training modeling teams, with a focus on Agentic AI, Muse and personal superintelligence. We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies that help interact with and understand our world. We are seeking individuals passionate about agentic AI, including but not limited to LLM agentic tool use, personalized AI agents, LLM agentic post-training, LLM reasoning/coding, and related areas. Our interns have an opportunity to make core algorithmic advances, prototype agentic features for Meta products, and apply their ideas at an unprecedented scale.
Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Responsibilities
- Develop novel state-of-the-art agentic AI algorithms and corresponding systems, leveraging machine learning and reinforcement learning techniques.
- Conduct research on agentic LLMs, agentic RL environments, LLM post-training, and related topics.
- Analyze and improve the efficiency, scalability, and stability of agentic AI algorithms and deployed systems.
- Advance the science and technology of intelligent, agentic machines capable of reasoning, tool use, and personalized interactions.
- Collaborate with researchers and cross-functional partners, including communicating research plans, progress, and results.
- Disseminate research results through publications, presentations, and open source contributions.
- When applicable, contribute to research that can be applied to Meta product development.
Qualifications
- Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Generative AI, or a relevant technical field
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
- Experience with Python
- Experience building systems based on machine learning and/or deep learning methods Intent to return to the degree program after the completion of the internship/co-op
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ICCV, ECCV, or similar
- Experience working and communicating cross functionally in a team environment
- Experience in advancing agentic AI techniques, including core contributions to open source libraries and frameworks in agentic LLMs or RL environments
- Publications or experience in agentic AI, LLMs, reinforcement learning, reasoning/coding, optimization, computer science, statistics, applied mathematics, or data science
- Experience solving analytical problems using quantitative approaches
- Experience setting up ML experiments and analyzing their results
- Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources
- Experience in utilizing theoretical and empirical research to solve problems
- Experience with deep learning frameworks