About the Role
You will build full-stack tools that help researchers, vendors, and domain experts create, review, submit, and monitor reinforcement-learning environments and tasks. You will own review and acceptance workflows, build authoring interfaces and reusable components, and improve the path from task ideas to trusted training data.
Requirements
- Experience shipping full-stack products from user interface through storage or services
- TypeScript
- React
- Node
- Python
- Go
- Experience building data-facing tools such as transcript viewers, diffing systems, review queues, observability products, or operational dashboards
- Experience building or maintaining a design system or component library
- Experience designing review, QA, moderation, fraud, or acceptance workflows
- Data-quality experience
- Experience with evaluations, graders, reinforcement learning, or data-quality systems is helpful
Responsibilities
- Create workflows for vendor task creation, iteration, submission, and acceptance into training
- Build tools to inspect and compare rollouts, transcripts, grader outputs, and task-quality signals
- Develop environment-health, failure-search, versioning, and catalog experiences
- Establish a shared component kit
- Build self-service task-authoring and improvement interfaces with inline quality checks
Hiring Process
Two or three short technical interviews focused on frontend craft and system design, followed by an onsite small project using real rollouts, idea discussion, and team meetings.