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Reality Labs (RL) teams are looking for exceptional interns to help us create next generation interaction technologies for virtual and augmented reality. Join a full-stack team working on computer vision, machine learning, and on-device deployment. We are looking for applications interested in (but not limited to) the following areas: -Geometry-aware vision models -Domain generalization -Domain adaptation -On-device model optimization -Vision foundation models. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Job Responsibility:
Develop and prototype advanced technologies in the domain of 3D computer vision and machine learning for AR/VR/MR related applications
Conduct in-depth literature reviews, build knowledge of the latest advancements in the target areas
Analyze the data characteristics, accuracy, efficiency, and generalizability of models to enhance model performance
Document and share research findings, contribute to technical reports, and potentially publish in academic or industry conferences/journals.
Requirements:
Currently has, or is in the process of obtaining, a PhD degree in EE/CS, Applied Math or a related STEM field
Experience in Python and common ML frameworks (e.g., PyTorch)
Experience in one or more of the following: computer vision, machine learning (e.g. domain generalization, domain adaptation, efficient deep learning), or computer graphics (e.g. appearance, geometry, physically-based modeling)
Strong analytical and problem-solving skills with a passion for innovation and cutting-edge research
Excellent written and verbal communication skills, with the ability to present complex ideas clearly and concisely
Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
Nice to have:
Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, or first-authored publications at leading journals or conferences such as CVPR, ECCV, ICCV, NeurIPS, ICML, ICLR, SIGGRAPH/SIGGRAPH Asia, ICRA, IROS, RSS, TPAMI, IJCV, etc
Contributions to open-source projects, publications, or relevant projects demonstrating expertise in synthetic image generation
Experience with cloud computing platforms and distributed computing for large-scale experiments
Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
Experiences working on high volume data with noisy labels