We are creating an AI system for analysts and scientists using a fundamentally new method for reasoning and representing knowledge. Our approach goes beyond modern LLMs by combining algorithms in symbolic ways, enabling capabilities such as multi‑step analysis, transparent and verifiable reasoning, and uncertainty assessment. We aim to support and automate analytical and research workflows in fields like finance, strategy consulting, engineering, material science, and more.

We are seeking software engineers with experience in transformer models to help build our inference pipeline. The role focuses on integrating pre‑trained transformer models with symbolic reasoning.

Our team is fully remote and primarily works within the CET time zone.

Useful experience:
• Work in natural language processing
• Building, training, and fine‑tuning deep learning models
• Deploying machine learning models at scale (serving, optimization)
• Familiarity with ML frameworks
• Keeping up with advances in deep learning and large language models

Responsibilities:
• Develop model evaluation frameworks based on task needs
• Build training and inference pipelines
• Integrate models as components of our production system
• Conduct research and document designs and findings
• Extend the system’s capabilities by applying state‑of‑the‑art techniques

More information about our work, culture, and sample tasks is available on our website:
What we do: https://planting.space/
How we work: https://planting.space/org
Team culture and example tasks: https://planting.space/joinus