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 efforts in building Personal Superintelligence within Meta Superintelligence Labs (MSL). We focus on turning ambiguous, real-world product problems into shipped systems and measurable improvements in frontier-model capabilities, including long-horizon agents, tool use, full-stack coding, search, and personalization. In this role, you will work across the full research-to-product stack—from user experiences, backend systems, and agent environments to data, evaluations, post-training, and deployment. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.
Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.
Responsibilities
- Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
- Perform research that can be applied to Meta product development.
- Work hands-on across the full LLM post-training stack.
- Build high-quality training data and design and run rigorous, product-relevant evaluations.
- Execute, analyze, and iterate on large-scale post-training runs.
- Advance long-horizon agentic capabilities, including tool use, full-stack coding, search, planning, and personalization.
- Research improved training, evaluation, synthetic-data generation, and data-curation strategies.
Minimum qualifications
- Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Generative AI, or 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, C++, C, Java or other related languages
- Experience building systems based on machine learning and/or deep learning methods
Preferred qualifications
- 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, CVPR, ICCV, ECCV, ACL or similar
- Experience working and communicating cross functionally in a team environment
- Experience in advancing AI techniques, including core contributions to open source libraries and frameworks in computer vision
- 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
Job description provided by Meta.
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