Research Scientist Intern, Egocentric Vision-Language Models (PhD)

Job description

The Meta Reality Labs Research Team brings together a world-class team of researchers, developers, and engineers to create the future of AR and VR. The Surreal Vision group at RL Research is seeking exceptional Research Scientists to research and help build the egocentric machine perception functionalities and digital twins of 3D scenes that will underpin future VR and contextual-AI-enabled AR devices. The Surreal group at Reality Lab Research is seeking outstanding Research Scientist Interns to advance the frontier of egocentric AI.

As an intern, you will tackle ambitious research challenges at the intersection of computer vision and natural language, contributing to the development of next-generation intelligent systems. Your research project may cover or relate to the following topics: -Advancing multi-modal understanding and reasoning in AI systems -Developing adaptive intelligent models -Mining temporal patterns in complex data -Designing proactive and context-aware AI models Our internships are twelve (12) to twenty four (24) weeks long and we have various start dates throughout the year.

Some projects may require a minimum of 24 consecutive weeks.

Responsibilities

Plan and execute innovative research to advance the state-of-the-art in egocentric AI, multi-modal understanding, and long-term reasoning. Collaborate with researchers and engineers to design, develop, and run experiments and prototype systems that push the boundaries of intelligent egocentric AI systems. Publish research findings in top-tier conferences and effectively present research outcomes to internal and external audiences.

Qualifications

Currently has, or is in the process of obtaining a PhD degree in the domain of Computer Vision, Natural Language, Reinforcement Learning or related field

• Knowledge in deep learning, computer vision, generative modeling, LLMs and VLMs Hands-on experience with implementing deep learning algorithms, large-scale training, benchmark and evaluation Programming experience in Python, deep learning frameworks such as Pytorch Experience working and communicating cross functionally in a team environment
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops or conferences such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, NAACL, ACL, EMNLP Experience building systems based on machine learning, reinforcement learning and/or deep learning methods Demonstrated SWE or research experience via an internship, work experience, coding competitions, widely used contributions in open source repositories (e.g.

GitHub), or top-tier publications Intent to return to a degree-program after the completion of the internship