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

Note: The job is a remote job and is open to candidates in USA. 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.

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

Skills

• 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)
• 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

Benefits

• Benefits

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