Apply on Employer Site

Meta · 22 hours ago

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

United States

Internship

Remote

Intern

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

2+ years exp

Meta is a leading technology company focused on connecting people and building communities through innovative applications and services. They are seeking a Research Scientist Intern to work on algorithm and hardware co-design for AI machine learning applications, with a focus on multitasking and multimodal understanding. The role involves researching and optimizing ML algorithms and collaborating with other researchers in the field.

Computer Software

Comp. & Benefits

Responsibilities

Research on design / model / execution of efficient ML algorithms

Research on novel ML or computational imaging algorithms for applications and optimize existing algorithms

Research on development and optimization of edge computing algorithms (ML and non-ML)

Collaboration with and support of other researchers across various disciplines

Communication of research agenda, progress and results

Prototyping, building and characterizing experimental systems and custom hardware

Qualification

Machine LearningComputer VisionPython/C++ ProgrammingDeep Learning FrameworksMultimodal ML AlgorithmsEdge Computing AlgorithmsSelf-Supervised LearningPrivacy Preserving MLPrototypingCollaborationCommunication

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 in multimodal ML algorithms (object detection, classification, tracking, keyword spotting, ASR, etc)

Experience in deploying ML algorithms to real-time with mobile platforms

Experience w/ NAS or developing and deploying algorithms with hardware constraints

Experience w/ pretraining using self-supervised learning

Experience w/ tuning LLM

Experience in privacy preserving ML algorithms

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