Spatial Reasoning Evaluation Specialist - Video RL

We are looking for Spatial Reasoning Evaluation Specialists to support a Video Reinforcement Learning (Video RL) program focused on evaluating AI-generated video outputs, autonomous agent trajectories, physical plausibility, temporal sequences, and spatial reasoning.

The role involves conducting detailed video evaluations to identify inconsistencies in motion, physics, action sequences, spatial relationships, and visual rendering. Candidates should have strong analytical and spatial-temporal reasoning abilities with exposure to areas such as Computer Vision, Reinforcement Learning, Robotics, Simulation, or Video Analysis.

Key Responsibilities:

• Step-Wise Trajectory Review: Conduct granular, frame-by-frame evaluations of agentic video rollouts, classifying physics anomalies, causal inconsistencies, and execution errors.
• Temporal Logic & Sequence Verification: Audit complex multi-event chronological sequences, ensuring correct action-effect causality and forward-backward temporal logic.
• Action Anticipation & Goal Reasoning: Evaluate whether autonomous agent behaviors align with specified multi-step goals, flagging path deviations or suboptimal sub-goals.
• Video Segmentation & Rendering QA: Verify spatial boundary boxes, optical flow fields, pixel-level semantic segmentation masks, and avatar skeletal motion rendering.
• Deep Rationale & Error Taxonomy: Author highly structured C1-level failure-mode analyses categorizing visual hallucinations, unnatural physics, and clipping artifacts.
• Golden Dataset Construction: Build hardened ground-truth validation sets and edge-case scenario libraries to boost programmatic verifier accuracy.

Candidate Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Physics, Data Science, Mathematics, or another STEM discipline, or equivalent technical experience.
• Exposure to Video Analysis, Computer Vision, Reinforcement Learning, Robotics, or simulation environments.
• Strong spatial and temporal reasoning skills.
• Excellent attention to detail and ability to focus on detailed evaluation tasks.
• Strong English communication and written reasoning skills.
• Basic knowledge of Python will be an added advantage.
• Familiarity with AI/ML concepts and advanced video annotation tools such as CVAT, Labelbox, or Roboflow will be preferred.