Research Scientist Intern, Foundation Model Optimization (PhD)

Meta; Menlo Park, Burlingame (CA, CA); On-site; USD 55,000 - 83,000; Full time

Job summary

Meta Reality Labs is offering a Research Scientist Intern position focused on language and vision model optimization. The intern will develop efficient large language models and foundation vision models, with emphasis on on-device performance and practical deployment.

Ideal candidates are PhD students in AI fields, experienced with PyTorch/JAX and transformers, and have a track record of research publications.

Qualifications

• PhD candidate in AI or related field.
• Must have valid work authorization at time of hire.
• Hands-on experience with deep learning algorithms and transformers.
• Experience with PyTorch and/or JAX libraries.
• Experience with Python and shell scripting.
• Experience with large-scale foundation model training and on-device optimization.
• Publications at CV/NLP/ML conferences/journals.
• Experience in LLM agents/orchestration, personalization, model compression, and efficient architectures.

Responsibilities

• Develop efficient LLMs and vision foundation models.
• Optimize models for on-device inference.
• Collaborate with Reality Labs teams on research goals.
• Contribute to publications and conference submissions.

Skills

Deep learning

Transformers

Multimodal modeling

Model compression

Efficient inference

Data-centric tuning

Education

PhD in AI or related field

Tools

PyTorch

JAX

Job description

Meta's mission is to give people the power to build community and bring the world closer together, and the Meta Reality Labs organization focuses on delivering this vision through AR/VR/SG devices.

Meta's Efficiency and On-Device AI team within the Reality Labs organization is seeking a Research Scientist Intern with a focus on language/vision model optimization. As a Research Scientist Intern, your primary objective is to develop cutting‑edge efficient LLMs and vision foundation models.

• Currently is in the process of obtaining a PhD in the field of Artificial Intelligence or related field
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
• Hands‑on experience in deep learning algorithms and techniques, e.g., transformers
• Experience with deep learning software libraries such as PyTorch/JAX
• Experience with scripting languages such as Python and shell scripts
• Intent to return to degree‑program after the completion of the internship
• Experience with large scale foundation model training and on‑device foundation model optimization
• Experience in one or more of: LLM agents and orchestration, personalization, model compression and efficient inference, efficient model architectures, multi‑modal modeling, data‑centric approaches for model tuning and evaluation
• Proven track record of publications at CV/NLP/ML conferences/journals such as NeurIPS, ICLR, ICML, CVPR, ICCV, ECCV, AAAI, ACL, EMNLP