You will focus on research and development of computer vision and machine learning algorithms toward analysis, segmentation, recognition, reconstruction, and interpretation of scenes captured by multi-modal data streams including video cameras and range sensors.
- Research and development of computer vision, machine learning, and optimization algorithms for feature selection, semantic segmentation, odometry, motion analysis, and recognition/tracking/forecasting of objects and persons.
- Design, development, and integration of the software systems and architectures necessary to realize research prototypes.
- Develop and evaluate metrics to verify reliability of the proposed algorithms.
- Participate in data collection, sensor calibration, and data processing.
- Participate in ideation, creation, and evaluation of related technologies in various domains including traffic scenes and indoor robotics.
- Contribute to a portfolio of patents, academic publications, and prototypes to demonstrate research value.
Must Have Skillsets:
- Strong familiarity with machine learning techniques pertaining to visual recognition and/or video analytics.
- 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.
- M.S. or PhD in computer science, electrical engineering, or related field.
- Experience in open-source Deep Learning frameworks such as TensorFlow or Caffe.
- Hands-on experience in handling multi-modal sensor data.
Location: Mountain View, CA