Reality Labs focuses on delivering Meta's vision through Virtual Reality (VR) and Augmented Reality (AR). Enabling compelling user experiences on Virtual and Augmented Reality devices requires innovation and co-design across all layers of stack from novel algorithms to custom silicon. The Meta AR/VR team is driving the state of the art forward with breakthrough work in computer vision, speech, virtual assistant, machine learning, mixed reality, graphics, displays, sensors, and new ways to map the human body among many others.We are seeking exceptional interns with a background in developing efficient models for AR/VR applications, including, but not limited to, computer vision, speech, sensor fusion, NLP, multi-modal AI. Our team focuses on developing state of the art models with tight constraints on memory and power and on model optimization techniques, e.g., sparsity, quantization, compression, network architecture search, tensor decomposition, etc. The ideal candidate will have practical experience in developing real time models that can achieve high accuracy under deployment constraints such as limited compute and memory resources.In this position, you will get exposure to the full stack from user experiences, algorithms down to hardware execution blocks. You will work with the domain experts to understand the challenges and build state-of-the-art networks to tackle them and then work with the software/hardware team to deploy these solutions on-device.Our internships are twelve (12) - sixteen (24) weeks long and we have various start dates throughout the year.

• Define, plan and execute cutting-edge deep learning research to advance AR/VR experiences
• Develop novel deep learning techniques to achieve state-of-the-art accuracy within the constraints of on-device and real-time execution on CNN, LLM and multimodal models
• Collaborate with other research scientists and software engineers to develop innovative deep learning techniques, such as quantization, compression, pruning etc, for vision, speech, user interface and other use-cases
• Collaborate with software and hardware engineers to develop tradeoff curves for accuracy vs the runtime resources/constraints such as latency, energy
• Communicate the experimental results and the recommendations clearly, both within the group as well as to the cross-functional groups

• Currently has, or is in the process of obtaining, a PhD degree in 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
• Experience in developing machine learning solutions for problems
• Experience and experience with deep learning framework for prototyping ideas
• Experience in building deep learning models for mobile or ultra lower power systems

• Intent to return to degree-program after the completion of the internship/co-op
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences in machine learning conferences such as ICML, ICLR, NeurIPS etc and/or journals
• Experience in optimizing deep learning networks for execution constraints besides just the final accuracy
• Background in computer vision, speech, natural language understanding, LLM training/inference, multi-modal AI, multi-sensor tracking/reconstruction, etc
• Experience working and communicating cross functionally in a team environment