Reality Labs Research is looking for an intern to help us develop the next generation assistance systems that guide the users in contextual and adaptive future AR/VR systems. In particular, we are seeking candidates who have experience with either of the following: multimodal learning, self-supervised learning, video understanding, representation learning. Work with researchers to help enable their work across the following research disciplines: - AI for Egocentric Representation Learning - Multimodal Learning Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, AI for Egocentric Representation Learning (PhD) Responsibilities
- Develop, implement, and evaluate methods for learning robust representations from multi-modal egocentric data (e.g., video, audio, inertial measurement units).
- Make use of Meta’s large infrastructure to scale and speed up experimentation.
- Write modular research code that can be reused in other contexts.
- Collaborate with other researchers.
- Work towards taking on big problems and deliver clear, compelling, and creative solutions to solve them at scale.
- The work should result in publishable research to appear in a top-tier ML or CV conference (e.g., NeurIPS, ICLR, CVPR, ECCV).
Minimum Qualifications
- Currently has or is in the process of pursuing a PhD in Machine Learning, Computer Vision, Speech Processing, Applied Statistics, Computational Neuroscience, or relevant technical field
- Research skills involving defining problems, exploring solutions, and analyzing and presenting results
- Proficiency in Python and Machine Learning libraries (Numpy, Scikit-learn, Scipy, Pandas, Matplotlib, Tensorflow, Pytorch, etc.)
- Understanding of at least one of the following areas: Transfer, few-shot, zero-shot, continual and/or online learning, self-supervised learning, or multi- or cross-modal learning
- 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 such as NeurIPS, ICML, ICLR, CHI, UIST, IMWUT, CVPR, ICCV, ECCV, AAAI, ICRA, SIGGRAPH, ETRA, or similar
- Experience with deep metric learning / neural net embedding methods
- Experience on vision based input recognition systems, such as hand tracking, body pose estimation
- Experience on working with time sequence form sensor data, such as IMU and audio
- Experience working and communicating cross functionally in a team environment
- Intent to return to degree program after the completion of the internship/co-op
