PlantingSpace

The role involves managing the development roadmap and leading quarterly planning to bridge the gap between strategic goals and technical execution. You will steer features from ideation to implementation while maintaining technical documentation and facilitating team communication.

Build and deliver end-to-end production-ready solutions for a system representing domain knowledge as probabilistic models. This includes defining features, writing design documents, and developing across the full stack from interactive interfaces to the backend.

The researcher will follow existing literature to formalize the categorical semantics of the probabilistic DSL, providing theoretical insights for implementation. They will also develop new models for real-world phenomena within the established framework and present results accessibly to experts in other fields.

Domain experts will collaborate on developing high-value use cases by integrating AI solutions directly into pilot users’ workflows, leveraging their industry networks for real-world adoption. This involves supporting a structured 4-stage development cycle from opportunity identification through to production transition.