Vacancy expired!
- Take ownership of mapping technologies in the next generation and make relentless efforts to research, evaluate, perfect, and promote proposed solutions within the organization.
- Research and development of next-generation mapping and localization solutions aiming at accurate and semantically correct scalable maps and localization with minimal supervision.
- Design, development, and integration of software systems necessary to realize research prototypes.
- Develop evaluation metrics to confirm the efficacy of proposed algorithms.
- Contribute to a portfolio of patents, academic publications, and prototypes to demonstrate research value.
- Be an essential member of a team of engineers and scientists that develop technologies for autonomous systems in a fast-paced software development environment.
- Deep understanding of classic SLAM pipeline such as feature extraction, triangulation, BA, loop closure, etc.
- Familiarity with recent advances in various SLAM topics, such as visual place recognition, long-term localization, semantic SLAM, topological mapping, distributed and incrementally learned maps, etc.
- Excellent software skills for real time operations.
- Ability to transfer conceptual models to working code in C or Python.
- Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents.
- Strong publication record in visual SLAM, computer vision or machine learning. At least 2-3 papers in this field, in reputable conferences.
- Experience with visual SLAM to do mapping and localization. Two methods: 1) classical approach 2) machine learning based methods b/c some complex situations like lighting and variations, things that require semantic scene understanding cannot be done with a classical method.
- Experience with machine learning based methods and state of the art computer vision SLAM technologies. Hands on experience, not just theoretical. Have research and implementation
- Ph.D. or M.S. in computer science, robotics, electrical engineering, or related field.
- Experience in Deep Learning frameworks such as TensorFlow or Pytorch.
- Familiarity with vehicle sensors and hardware, including cameras, LiDAR, GPS, CAN, IMU, USB, Ethernet.
- Extensive hands-on experience in real-world robotics applications and robot operating system (ROS).
Vacancy expired!