About the role#
The Efficiency and On-Device AI team at Meta is looking for a PhD student to help develop efficient language and vision foundation models. You will work on algorithms and infrastructure that allow these models to run on resource-constrained devices like mobile phones and AR/VR hardware.
What you'll do#
- Perform research on LLMs and vision models with the goal of publishing in top-tier conferences.
- Build optimization algorithms to support model deployment on devices.
- Study how models interact with assistant systems, including memory, planning, and tool use.
- Explore new architectures, personalization, and compression techniques.
- Work alongside cross-disciplinary research and engineering teams.
What you'll need#
- Currently pursuing a PhD in Artificial Intelligence or a related field.
- Hands-on experience with deep learning techniques, specifically transformers.
- Proficiency with Python, shell scripts, and deep learning libraries like PyTorch or JAX.
- Ability to obtain and maintain work authorization in the United States.
- Preferred: A track record of publications at conferences such as NeurIPS, ICLR, ICML, CVPR, ICCV, ECCV, AAAI, ACL, or EMNLP.
- Preferred: Experience with large-scale training, on-device optimization, or LLM agents.
- Preferred: An intent to return to your degree program after the internship.
Location & details#
- This is a full-time, paid internship.
- The role is based on-site in Sunnyvale, Menlo Park, or Burlingame, California.
- The internship term is rolling.
About Meta
Meta develops software and social media applications. It operates platforms such as Facebook, Messenger, Instagram, and WhatsApp. The company maintains headquarters in Menlo Park, California. Current work focuses on augmented and virtual reality alongside artificial intelligence and machine learning.
How to get in at Meta
Landing an internship at Meta requires a proactive approach to the application process. Intern Insider sends an instant alert the moment a role matching your target is published, allowing you to apply among the first. Early applicants often have their materials reviewed before the applicant pool grows significantly. You can use Intern Insider to surface the recruiters behind specific roles at Meta. Reaching out directly to these individuals to ask about the position or a referral often improves your response rates compared to applying into a queue.
