Vacancy expired!
Computer Vision Research Engineer: Scene Understanding and Semantic SLAM for Global Automotive Company in San Jose, CA
Summary: Join an innovation team with a global automotive company as the Computer Vision Research Engineer: Scene Understanding and Semantic SLAM. This position focuses on developing computer vision and machine learning algorithms for visual and spatial understanding of scenes for next generation mobility systems. Initial emphasis includes development of visual-inertial mapping and localization system that creates and updates maps that are stable over long-term and encode semantic, dynamic, and anomalous events. Responsibilities include proposing, designing and implementing scalable systems that are implemented on actual prototypes. The candidate is expected to take ownership of the proposed solution and make relentless efforts to evaluate, perfect and promote it within the organization. Responsibilities:- Design, development, and integration of Visual-Inertial SLAM systems.
- Design and development of Deep Neural Networks for semantic understanding of visual scenes.
- 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 autonomous driving technologies in a fast-paced software development environment.
- Familiarity with classical SLAM pipeline such as Feature Extraction, Triangulation, Graph Optimization, Loop Closure, etc.
- Experience in scene representation and spatial relation modeling.
- Ability to transfer conceptual models to working code in C and/or Python.
- Experience with Deep Learning frameworks TensorFlow and/or PyTorch.
- M.S. or equivalent skill in Computer Science, Robotics, Electrical Engineering, or related field.
- Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents.
- Familiarity with recent advances in Semantic SLAM, Visual Place Recognition, Long-Term Localization, Distributed Mapping, etc.
- Familiarity with Vehicle Sensors and Hardware, including Cameras, GPS, IMU, USB, CAN, Ethernet, Embedded Computers.
- Experience with software engineering tools and processes (Git, Jira, Agile, Scrum, Kanban, etc.).
- Extensive hands-on experience in real-world robotics applications and robot operating system (ROS).
Vacancy expired!