About The Opportunity

A fast-scaling AI research and evaluation lab in the Generative AI & Spatial Reasoning domain, we build and benchmark next-gen video-based reinforcement learning (RL) agents that perceive, plan, and act in 3D environments. Our work powers real-world embodied AI applications—from robotics navigation to autonomous systems—by rigorously testing how models understand spatial relationships, motion logic, and scene dynamics from video input. We're hiring a Spatial Reasoning Evaluation Specialist to design, execute, and scale high-fidelity human-in-the-loop evaluations for video RL models.

Role & Responsibilities

Design and implement standardized evaluation protocols to assess spatial reasoning performance of video RL agents across tasks like path planning, object interaction, and scene navigation.
Annotate, curate, and label video datasets to create ground-truth benchmarks for agent evaluation, with emphasis on temporal-spatial consistency and action causality.
Run human-in-the-loop experiments comparing agent output against human baseline performance using structured scoring rubrics and UI tools.
Identify failure modes, edge cases, and spatial reasoning gaps in agent behavior and document findings for research and engineering teams.
Collaborate with ML researchers to iterate on evaluation metrics, refine task design, and improve benchmark robustness.
Build and maintain evaluation dashboards to track agent performance trends, score distributions, and spatial reasoning drift over time.

Skills & Qualifications

Must-Have
PyTorch
OpenCV
Video annotation tools (e.g., CVAT, Labelbox)
Spatial reasoning task design
Human-in-the-loop evaluation frameworks
Reinforcement learning basics (e.g., PPO, DQN, env interaction)
Python scripting for data validation & reporting
3D scene understanding (e.g., coordinate frames, depth maps, camera poses)
Preferred
Experience with embodied AI platforms (e.g., Habitat, AI2 Thor, Unity ML-Agents)
Familiarity with RLlib or RL frameworks for agent benchmarking
Background in cognitive science or psychophysics of spatial reasoning

Benefits & Culture Highlights

Work directly with cutting-edge video RL models shaping the future of embodied AI.
On-site innovation lab environment in India with access to high-end annotation tools and compute infrastructure.
Opportunity to co-author research evaluations and contribute to public benchmarks in spatial reasoning.

Skills: design,annotation,agents,research,video,learning,models,edge,3d,evaluations

Spatial Reasoning Evaluation Specialist (VIDEO RL)