Research Scientist Intern, Multimodal and Multitasking Machine Learning (PhD)

Meta•Redmond, WA

2d•$7,650 - $12,667

About The Position

Meta Reality Labs Research seeks PhD-level scientists and researchers interested in algorithm and hardware co-design, AI/ML acceleration, efficient sensing, and machine learning algorithms for AR/VR applications. The team develops hardware-optimized algorithms for machine perception and systems that can bring LLM-powered AI assistants to wearable devices. This internship focuses on foundational AI technologies supporting assistant functionality, including multitasking, multimodal understanding (such as audio, visual, and spatial), and privacy. Internships last 12 to 24 weeks and have various start dates throughout the year.

Requirements

Currently pursuing or in the process of obtaining a PhD in Computer Science, Electrical Engineering, or a related field.
Must obtain work authorization in the country of employment by the time of hire and maintain it during employment.
At least 2 years of research experience in developing machine learning and computer vision models, optimizing edge computing algorithms, or distributed compute architectures.
At least 2 years of programming experience in Python or C++.
Experience with deep learning frameworks such as PyTorch or TensorFlow.

Nice To Haves

Experience with multimodal ML algorithms, such as object detection, classification, tracking, keyword spotting, or ASR.
Experience deploying ML algorithms for real-time use on mobile platforms.
Experience with neural architecture search (NAS) or developing and deploying algorithms under hardware constraints.
Experience with pretraining using self-supervised learning.
Experience tuning LLMs.
Experience with privacy-preserving ML algorithms.
A record of significant results demonstrated through first- 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 completing the internship.

Responsibilities

Research the design, modeling, and execution of efficient ML algorithms.
Research novel ML or computational imaging algorithms for applications and optimize existing algorithms.
Research the development and optimization of edge computing algorithms, including ML and non-ML algorithms.
Collaborate with and support researchers across disciplines.
Communicate research agenda, progress, and results.
Prototype, build, and characterize experimental systems and custom hardware.