About Us
Deccan AI Experts is a pioneering company founded by IIT Bombay and IIM Ahmedabad alumni, with a strong founding team from IITs, NITs, and BITS. We specialize in delivering high-quality human-curated data, AI-first scaled operations services, and more. Based in SF and Hyderabad, we are a young, fast-moving team on a mission to build AI for Good, driving innovation and positive societal impact.
About the Role:
We are hiring an RL Environment Annotator (Notion) to help construct and evaluate reinforcement learning (RL) environments inside Notion. You will create realistic workspace structures, databases, workflows, and collaboration systems, then observe AI agent behavior and correct actions using precise tool instructions and arguments.
Key Responsibilities:
- Create realistic Notion workspaces including databases, pages, templates, task systems, relations, and collaborative workflows.
- Configure and manage database properties, linked views, filters, permissions, formulas, rollups, and workspace structures.
- Observe AI agent behavior while interacting with Notion environments and provide detailed corrections for inaccurate or incomplete actions.
- Validate proper handling of page operations, database updates, relations, automations, permissions, and workflow logic.
- Document and annotate tool interactions, execution steps, and environment states for RL training datasets.
- Design business and productivity scenarios that test project management, documentation, knowledge management, and operational workflows.
Required Experience:
- Experience as a Notion Administrator, Workspace Manager, Operations Associate, or Productivity Tools Specialist.
- Strong understanding of Notion databases, relations, rollups, formulas, templates, views, permissions, and workspace organization.
- Familiarity with workflow design, task management systems, and collaborative productivity environments.
- IT administration, operations, knowledge management, or productivity tooling background preferred.
- Ability to evaluate workflow logic, identify execution errors, and improve environment design for AI training systems.
Why Join Us
- Work on cutting-edge AI agent training involving modern productivity and collaboration platforms.
- Flexible, remote work with a highly skilled technical and research team.
- Contribute to foundational datasets powering next-generation AI workflow automation.
- Gain exposure to advanced RL-based agent evaluation and workspace simulation systems.
