Research Engineer - Robotics
San Francisco, CA
Full - Time
Imagine taking autonomous vehicle technology from ‘100 vehicles in a couple of geo-fenced regions’ to ‘1 million vehicles across 100+ cities’. A major bottleneck towards realizing this is in large-scale multi-modal mapping. Maps are a composite of relevant prior information: high-resolution scans of the ground surface, geometric data accurate to the centimeter, driving-logs and accurately labelled environmental elements (such as lane markers, crosswalks and signs).
Explorer.ai is a young company - started in Aug 2017; and has very quickly started working with 10+ autonomous vehicle teams on their mapping challenges. We are looking for really smart software engineers who want to enable the future of autonomous vehicles across the world. You will build robust and city scale SLAM implementations that power efficient building and updating of geometric maps of real-world road environments.
- Build a Robust Mapping platform to create and serve geometric maps using sensor fusion.
- Improve existing SLAM, localization and global optimization methods for efficient and real-time map building and updating.
- Multi-vehicle collaborative map creation; cross modal transfer learning.
Skills we are looking for:
- Hands on experience making robots move.
- Sound understanding of localization, mapping and SLAM.
- Experience with SLAM optimization for autonomous vehicles.
- Familiarity with Deep Learning for multimodal understanding.
- Familiarity with Hybrid Hardware Architectures.
- MS/PhD in Robotics, Computer Science or equivalent
The data is incontrovertible that diversity leads to higher quality innovation. Consequently, we actively encourage people of all gender, backgrounds and experiences to apply.