Jobs at PlantingSpace

The Applied Category Theory Researcher will develop category theoretic models for real-world phenomena, formalizing categorical semantics for probabilistic programming and improving the implementation based on theoretical insights.

Collaborate with engineers to identify, validate, specify, and implement high-value use cases using the company's symbolic probabilistic modeling system. Provide deep domain expertise, statistical modeling guidance, and industry contacts to recruit pilot users. Help integrate pilot solutions into users' workflows and support transition from pilot to production, working as a contracted practitioner with revenue-share opportunities.

Develop and implement a program synthesis pipeline, design complex algorithms, and work collaboratively on features and improvements in a remote setting.

Develop models and algorithms for statistical inference and machine learning, implement Bayesian methods, and enhance software systems using programming languages.

This is a general opening for experienced academics or technologists to submit applications for future job opportunities. Candidates are encouraged to describe their relevant experiences for assessment.

Researchers will develop numerical-analytical models of learning algorithms, analyze existing literature, prove algorithm properties, and design experiments. Responsibilities include writing clean code and collaborating with team members.

The Engineering Program Lead will manage the development roadmap, lead quarterly planning, coordinate features from idea to implementation, maintain documentation, facilitate communication, and contribute to development tasks.

Develop and productize an AI system for quantitative applications by implementing demos, optimizing performance, and collaborating on feature definitions.