
Research Scientist Intern, Efficient World Foundation Models (PhD)
Required skills
- ML algorithms
- computational imaging
- generative AI
- edge applications
- edge computing
- distributed computing
- hardware constraints
- real hardware
- Python
- C++
Nice to have
- Multi-Modal LLM
- world foundation models
- self-supervised learning
- embodied AI
- generative models
- visual generation
Role summary
Meta Reality Labs Research is seeking PhD candidates for an internship focused on efficient AI algorithms and machine learning acceleration for wearable smart glasses. The role involves researching and developing state-of-the-art system-optimized algorithms for machine perception, with a focus on world foundation models, multitasking, multimodal understanding, and generative models for AI assistants and embodied AI. Interns will work on designing, modeling, and executing efficient ML algorithms, optimizing them for edge and distributed computing, and prototyping experimental systems with real hardware. Collaboration and communication of research findings are key aspects of the role. The internship duration is 12-24 weeks.
Responsibilities
- Research on design / model / execution of efficient ML algorithms.
- Develop and optimize novel ML, computational imaging, and generative AI algorithms for edge applications.
- Research on development and optimization of edge and distributed computing algorithms.
- Collaboration with and support of other researchers across various disciplines.
- Communication of research agenda, progress and results.
- Prototyping, building and characterizing experimental systems with real hardware.
Minimum Qualifications
- Currently has, or is in the process of obtaining a PhD in the fields of Computer Science, Electrical Engineering, or related field
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
- 2+ years research experience in one or more of the following: developing machine learning and computer vision models, optimization of edge computing algorithms, or distributed compute architectures
- 2+ years experience programming in Python/C++
- Experience with Deep Learning frameworks (Pytorch, TensorFlow, etc)
Preferred Qualifications
- Experience with customizing Multi-Modal LLM
- Experience with world foundation models, self-supervised learning, and embodied AI
- Experience with generative models and high-quality visual generation
- Experience in deploying ML algorithms for real-time execution on mobile and distributed platforms
- Experience with NAS or developing and deploying algorithms with hardware constraints
- Proven track record of achieving significant results, as demonstrated by first- and/or co-authored publications at leading workshops or conferences (e.g., CVPR, ICCV, TinyML, NeurIPS, ICML), patents, or grants
- Intent to return to the degree program after the completion of the internship
$7,650/month to $12,667/month + benefits
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