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Responsibilities
- Conduct research on multi-modal learning, including vision-language models, audio-visual understanding, and cross-modal reasoning
- Develop novel architectures and training methodologies for models that integrate and reason across multiple modalities
- Design and execute experiments to evaluate multi-modal model capabilities and identify areas for improvement
- Publish research findings at top-tier conferences and contribute to Meta's research community
- Collaborate with cross-functional teams to translate research innovations into product applications
- Mentor and guide other researchers on multi-modal AI projects
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field
- Experience with multi-modal learning, vision-language models, or cross-modal representation learning demonstrated through publications or projects
- Experience programming in Python and with deep learning frameworks such as PyTorch
- Experience with large-scale model training and distributed computing
Preferred Qualifications
- Experience building end-to-end multi-modal systems from research to production
- Experience with video understanding or audio-visual learning
- Publications at venues such as NeurIPS, ICML, ICLR, CVPR, ACL, or EMNLP focused on multi-modal learning
- Experience with large language models, vision transformers, or foundation models
$154,000/year to $217,000/year + bonus + equity + benefits
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