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

Meta - Redmond, WA

Full-time - Intern

Redmond, WA

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About the position

The Research Scientist Intern position at Reality Labs Research focuses on developing advanced assistance systems for augmented and virtual reality (AR/VR) environments. The intern will engage in research related to AI for Egocentric Representation Learning and multimodal learning, contributing to projects that aim to create robust representations from multimodal egocentric data. This role is designed for PhD candidates and emphasizes collaboration with researchers to produce publishable work in top-tier machine learning and computer vision conferences.

Responsibilities

• Develop, implement, and evaluate methods for learning robust representations from multi-modal egocentric data (e.g., video, audio, inertial measurement units).
• Utilize 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 solving significant problems and deliver clear, compelling, and creative solutions at scale.
• Aim for the work to result in publishable research in top-tier ML or CV conferences.

Requirements

• Currently pursuing or has a PhD in machine learning, computer vision, speech processing, applied statistics, computational neuroscience, or a relevant technical field.
• Excellent research skills in 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 transfer, few-shot, zero-shot, continual and/or online learning, self-supervised learning, or multi- or cross-modal learning.
• Strong interpersonal skills for cross-group and cross-culture collaboration.
• Must obtain work authorization in the country of employment at the time of hire and maintain it during employment.

Nice-to-haves

• Proven track record of significant results demonstrated by grants, fellowships, patents, or first-authored publications at leading workshops or conferences.
• Experience with deep metric learning / neural net embedding methods.
• Experience with vision-based input recognition systems, such as hand tracking and body pose estimation.
• Experience working with time sequence data from sensors, such as IMU and audio.
• Experience in cross-functional team environments.
• Intent to return to degree program after the internship/co-op.

Benefits

• $7,500/month to $11,333/month compensation
• Health insurance
• Paid holidays
• Flexible scheduling
• Professional development opportunities