[Remote] Applied Research Engineer – Robotics Data & ML at Turing

The Applied Research Engineer will define and evolve labeling schemas for robotic perception tasks, including 2D/3D detection, segmentation, grasp and manipulation point annotations, scene affordances, human-robot interaction, and sensor fusion. They will align annotation strategies with key robotics benchmarks and downstream model use cases like RL, imitation learning, and vision-based control. The role involves fine-tuning and evaluating small ML models for targeted robotics tasks under senior guidance and performing basic experiments to assess data effectiveness. Additionally, the engineer will contribute to quality control processes by building checklists, gold sets, and feedback loops, and collaborate with ML, robotics, and data labeling teams to translate model and benchmark requirements into clear data specifications. This includes writing clear documentation and presenting technical updates to collaborators and stakeholders.