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Meta · 1 day ago

Research Scientist Intern, Efficient World Foundation Models (PhD)

Burlingame, CA

Internship

Onsite

Intern

$7,313/mo - $12,134/mo

2+ years exp

Meta is a company focused on connecting people and building communities through innovative technologies. They are seeking a Research Scientist Intern to work on efficient AI algorithms and machine learning applications for wearable smart glasses, contributing to the development of advanced systems for AI assistants.

Computer Software

Comp. & Benefits

Responsibilities

Research on design / model / execution of efficient ML algorithms

Develop and optimize novel ML, computational imaging, and generative AI algorithms for edge applications

Research on development and optimization of edge and distributed computing algorithms

Collaboration with and support of other researchers across various disciplines

Communication of research agenda, progress and results

Prototyping, building and characterizing experimental systems with real hardware

Qualification

Machine LearningComputer VisionPythonDeep Learning frameworksGenerative ModelsEdge ComputingDistributed ComputingMulti-Modal LLMSelf-Supervised LearningReal-time ExecutionPrototypingCollaborationCommunication

Required

Currently has, or is in the process of obtaining a PhD in the fields of 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

2+ years research experience in one or more of the following: developing machine learning and computer vision models, optimization of edge computing algorithms, or distributed compute architectures

2+ years experience programming in Python/C++

Experience with Deep Learning frameworks (Pytorch, TensorFlow, etc)

Preferred

Experience with customizing Multi-Modal LLM

Experience with world foundation models, self-supervised learning, and embodied AI

Experience with generative models and high-quality visual generation

Experience in deploying ML algorithms for real-time execution on mobile and distributed platforms

Experience with NAS or developing and deploying algorithms with hardware constraints

Proven track record of achieving significant results, as demonstrated by first- and/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 the completion of the internship