Research Engineer - Robotics AI

Preferred

• Experience with real-world product development and deployment of autonomous systems.
• Hands-on experience in reinforcement learning for behavior or motion planning or other applicable contexts and familiarity with common RL techniques (e.g. PPO, DQN, DDPG).
• Hands-on experience building and applying multimodal transformer-based sequence-to-sequence models, especially multimodal vision-language-action models.
• Hands-on experience in computer vision and deep learning, with work in any of the following areas: multimodal transformers, multimodal language models, diffusion models, NeRF, gaussian splatting, object detection / segmentation, 3D scene understanding, sensor calibration, SfM, voxel/BEV grid-based feature representation
• A strong portfolio of publications in premier machine learning, deep learning, robotics and computer vision journals and conferences.