Research Scientist Intern PhD, Applied Research

Meta was built to help people connect and share. With over a billion users and more than fifty offices worldwide, a career at Meta offers countless ways to make an impact in a fast-growing organization.

Meta is seeking Research Interns to join our Products and Applied Research team. We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We seek individuals passionate about areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.

Our internships are twelve (12) to twenty-four (24) weeks long, with various start dates throughout the year.

Responsibilities

• Develop novel state-of-the-art generative AI algorithms and corresponding systems, leveraging various deep learning techniques.
• Help analyze and improve safety and robustness of deployed algorithms based on the project.
• Perform research to advance the science and technology of intelligent machines.
• Collaborate with researchers and cross-functional partners, including communicating research plans, progress, and results.
• Disseminate research results and publish research that can be applied to Meta product development.

Qualifications

• Currently pursuing or in the process of obtaining a Ph.D. in Computer Science, Computer Vision, Audio Processing, 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.
• Research experience in machine learning, deep learning, computer vision, and/or natural language processing.
• Experience with programming languages such as Python, C++, C, Java, or other related languages.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Intent to return to the degree program after completion of the internship/co-op.
• Proven track record of significant results demonstrated by grants, fellowships, patents, or first-authored publications at leading workshops or conferences (e.g., NeurIPS, ICLR, AAAI, RecSys, KDD, IJCAI, CVPR, ECCV, ACL, NAACL, EACL, ICASSP, or similar).
• Experience working and communicating cross-functionally in a team environment.
• Publications or experience in machine learning, AI, computer vision, 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-dimensional data from varying sources.
• Experience in utilizing theoretical and empirical research to solve problems.
• Experience with explainable AI methods and topics around LLM safety alignment.
• Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open-source repositories (e.g., GitHub).