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