About the role#
This internship focuses on the compression of neural and learned representations for AI, Augmented Reality, and Virtual Reality. As high-capability models grow, split inference architectures become necessary to manage latency and power constraints. You will work on developing compression techniques for non-human-consumed data, such as latent tensors, Gaussian splats, and feature maps, to improve the efficiency of split-inference systems.
What you'll do#
- Explore methods for processing, compressing, and streaming neural representations.
- Identify opportunities to improve compression efficiency or quality.
- Build working prototypes of proposed algorithms with your peers.
- Communicate your research progress and final results.
- Conduct literature reviews and benchmark your models against traditional compression methods.
What you'll need#
- Currently pursuing a PhD in Image and Video Processing, Signal Processing, Information Theory, Machine Learning, Computer Graphics, or a related field.
- Coding experience in C, C++, or Python.
- Experience in image and video processing.
- A proven track record of research results, such as patents, grants, fellowships, or first-authored publications at relevant conferences.
- Knowledge of neural networks, learning-based compression, and existing standards like H.26x, VPx, JPEG, or MPEG PCC.
- Intent to return to your degree program after the internship.
Location & details#
- Location: Redmond, Washington.
- Work Modality: On-site.
- Employment: Full-time intern.
- Term: 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.
