Research Scientist Intern, MSL Agents (PhD)

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.

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 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