Research Scientist Intern, Perception – Meta

Research Scientist Intern, Perception (PhD) Responsibilities

• Perform research that enables learning the semantics of data (primarily images, video, 3D structures, text, and other modalities like audio).
• Brainstorm with research mentors, review literature and existing solutions of a challenging real-world research problem.
• Develop novel solutions, implement prototypes, and perform extensive experiments to test the proposed solutions in meaningful benchmarks and metrics, analyze the results and verify the conclusions.
• Contribute to ongoing research projects and impactful technology releases.
• Draft and polish research publications.
• Present research outcomes to internal and/or external audiences.

Minimum Qualifications

• Currently has, or is in the process of obtaining, a PhD degree in Computer Vision, Machine Learning, Artificial Intelligence, or relevant technical field.
• Research and/or work experience in Computer Vision. In particular: recognition, 2D/3D localization, segmentation and tracking of objects, people, and activities, and/or 3D pose estimation and 3D reconstruction, and/or grounded image and video understanding, egocentric vision, vision-language foundational models, un-/semi-/supervised representation learning, and related areas.
• Research and/or work experience in Machine Learning or Deep Learning with applications to perception.
• Experience in Python, C++, or other related languages.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.

Preferred Qualifications

• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences in Computer Vision (CVPR, ECCV, ICCV), Speech & Language (ACL, EMNLP, ICASSP, NAACL), Machine Learning (NeurIPS, ICLR, ICML, AAAI) or Computer Graphics (SIGGRAPH).
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
• Experience advancing AI techniques, including contributions to open source libraries and frameworks.
• Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources.
• Experience in utilizing theoretical and empirical research to solve problems.
• Experience working and communicating cross functionally in a team environment.
• Intent to return to the degree program after the completion of the internship/co-op.