Research Scientist Intern, AI Alignment

Meta•Boston, MA

3d•$7,650 - $12,667

About The Position

Meta Fundamental AI Research (FAIR) is seeking Research Scientist Interns to advance research in AI alignment and machine learning systems. Teams work to make AI systems more reliable, efficient, measurable, and aligned with human intent. Research areas include reasoning and agents, evaluation and robustness, efficiency, safety and security, privacy, world modeling, and societal dimensions of AI governance. Interns join a multidisciplinary team of research scientists and engineers and pursue an open research question from problem framing through experimentation to publication. They are expected to lead their own mentored research projects rather than execute a predefined task list. Applicants from technical backgrounds including machine learning, natural language processing, computer vision, reinforcement learning, statistics, and social sciences as applied to AI systems are encouraged. Internships last 12 to 24 weeks, with various start dates throughout the year.

Requirements

Currently have or be in the process of obtaining a Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a relevant technical field.
Obtain work authorization in the country of employment by the time of hire and maintain ongoing work authorization during employment.
Experience with Python, C++, C, Java, or another related programming language.
Experience with deep learning frameworks such as PyTorch or TensorFlow.
A first-author publication at a top-tier ML, NLP, or systems venue (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ICCV, MLSys) or equivalent.

Nice To Haves

Intent to return to a degree program after the internship or co-op.
A track record of significant results demonstrated through grants, fellowships, patents, or publications at leading workshops or conferences such as NeurIPS, ICLR, AAAI, RecSys, KDD, IJCAI, CVPR, ECCV, ACL, NAACL, EACL, ICASSP, CCS, IEEE S&P, MLSys, or similar.
Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches.
Experience building large-scale machine learning systems and training with large datasets.
Experience communicating complex research clearly, precisely, and in an actionable manner.
Demonstrated software engineering experience through an internship, work experience, coding competitions, or widely used open-source contributions.
Experience working and communicating cross-functionally in a team environment.

Responsibilities

Develop novel state-of-the-art algorithms and corresponding systems using deep learning techniques.
Analyze and improve algorithms and systems, including their efficiency, scalability, stability, fairness, security, and privacy.
Conduct state-of-the-art research to advance machine learning and artificial intelligence.
Collaborate with researchers and cross-functional partners, communicating research plans, progress, and results.
Publish research results and contribute to research applicable to Meta product development.