Scientist: Video/Multimodal Data Analytics
Scientist: Video/Multimodal Data Analytics (Job Number: P17F05)
Mountain View, CA

This position offers the opportunity to conduct innovative research on a broad set of problems related to multi-modal temporal segmentation.

Key Responsibilities:


  • Propose, create, and implement supervised and unsupervised data segmentation/clustering algorithms from multimodal and multisensory data streams obtained from traffic scenes.
  • Develop and evaluate metrics to verify reliability of the proposed algorithms.
  • Participate in ideation, creation, and evaluation of related technologies in various domains other than traffic scenes, including temporal segmentation of human activities.
  • Contribute to a portfolio of patents, academic publications, and prototypes to demonstrate research value.
  • Participate in data collection, sensor calibration, and data processing.
  • Participate in software development and implementation on various experimental platforms.



  • PhD in computer science, electrical engineering, or related field.
  • Research experience in computer vision, machine learning, and multi-modal signal processing.
  • Strong familiarity with machine learning techniques pertaining to sequential data processing.
  • Preferred hands on experience in handling multi-modal sensor data.
  • Preferred experience in open-source Deep Learning frameworks such as TensorFlow or Caffe.
  • Highly proficient in software engineering using C++ and Python.
  • Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents.
  • Strong publication record in one or more of the following areas: computer vision, machine learning, or computer vision.


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