Research Scientist Intern, AI for Egocentric Representation Learning (PhD)
Meta

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. Some projects may require a minimum of 16 consecutive weeks.

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.
• Excellent 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).
• Deep 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.
• Interpersonal skills: cross-group collaboration and cross-culture collaboration.
• 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.
• Availability for minimum 16 consecutive week internship.

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