Vacancy expired!
- Research and development of video-based computer vision algorithms that enable interpretation and understanding of complex traffic scenes involving high degree of interaction between road users and the environment for various driving assistance technologies.
- Support creation of benchmark datasets for training and evaluation of algorithms, including experiment design, sensor calibration, managing data collection, creating data annotation guidelines, and managing annotation work with outside vendors.
- Design, development, and integration of software systems and architectures necessary to realize research prototypes.
- Develop and evaluate metrics to verify reliability of proposed algorithms.
- Contribute to a portfolio of patents, academic publications, and prototypes to demonstrate research value.
- Should be very good software architect/ developer to create prototypes and evaluate metrics to verify reliability or proposed algorithms.
- Support the scientists in creating the publications/ patents/ prototypes.
- Prefer more research engineering skills but with knowledge and background in the field to read papers/ articles and implement them
- Strong familiarity with machine learning techniques pertaining to visual scene understanding.
- Familiarity with scene modeling and interpretation using spatiotemporal graphs, scene graphs, graph convolution networks, or similar graphical modeling techniques.
- Experience in open-source Deep Learning frameworks such as TensorFlow or Pytorch.
- Highly proficient in software engineering using C and Python.
- Excellent software architect or developer background creating prototypes.
- Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents.
- M.S. in computer science, electrical engineering, or related field.
- Hands-on experience in handling multi-modal sensor data.
- Strong publication record in computer vision or machine learning.
- Ph.D. in computer science, electrical engineering, or related field.
Vacancy expired!