Research Robotics/Computer Vision Engineer

At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.

Skild AI, Inc. seeks a Research Robotics/Computer Vision Engineer in San Mateo, CA responsible for developing perceptive, intelligent, and adaptable robotic systems capable of learning and performing tasks with a focus on 3D computer vision and autonomous navigation. This includes designing perception pipelines, optimizing SLAM systems, and creating learning-based algorithms for robust robotic control in real-world environments. Specific duties include: (i) implementing perception on robots to enable safe exploration and navigation in real world environments in collaboration with the locomotion team; (ii) reconstructing an entire scene in 3D using monocular images, estimating camera poses, optimizing and streamlining 3D SLAM; (iii) developing a set of software tools for localization of a robot using only visual inputs; (iv) building robust software to enable life-long mapping on a robot via optimally merged pose-graphs; (v) visual servoing wrt objects detected/ tracked to control robot motion; (vi) researching novel techniques to detect and cater to glare during robotic mapping and navigation; (vii) building infrastructure and pipeline and collecting data to enable streaming of hand movements for training robot manipulation tasks such as pick and place; and (viii) maintaining a camera and 2D lidar based navigation stack, including fixing bugs, adding new customer feature requests, and ensuring successful deployments.