Symbrosia
AI & Data Systems Fellow
About the Organization
Symbrosia is a Hawaiʻi-based cleantech aquaculture startup using the red seaweed Asparagopsis taxiformis to reduce methane emissions from livestock. Our feed additive, SeaGraze®, has been shown to cut methane by over 80% and increase productivity.
Fellowship Description:
We’re seeking a technical and strategic AI & Data Systems Fellow to drive Symbrosia’s digital transformation and data independence. This role has two critical objectives: optimizing internal operational efficiency through AI analysis and developing an in-house seaweed cultivation tracking solution.
The Fellow will lead the transition of our seaweed cultivation analytics from an external provider to an internally owned system. Working directly with our existing database, you will replicate and improve upon insights regarding batch tracking and culture performance. Simultaneously, you will act as an automation strategist, analyzing internal workflows to determine the Return on Investment (ROI) of various AI tools to streamline operations.
Responsibilities:
Seaweed Cultivation AI Chatbot
-Develop a deep technical understanding of Symbrosia’s seaweed cultivation process, assessing how parameter changes affect production and identifying operational constraints.
-Evaluate the existing external AI platform and produce a report on key functions such as batch tracking, culture performance, cycle durations, and Daily Growth Rate (DGR) logic.
-Design and build an internal chatbot using Symbrosia’s database, incorporating identified system limits.
-Choose a hosting environment and ensure the tool provides accessible, natural-language data interaction for non-technical users.
AI Operations & ROI Analysis
-Work with team leads to map workflows, identify pain points, and define where AI assistants can add value.
-Compare AI automation options, assess fit for needs, and calculate ROI versus manual processes.
-Create a roadmap for deploying selected AI agents, from pilots through full integration.
-Deliver data-driven guidance on future AI “build vs. buy” decisions.
Qualifications:
-Currently enrolled in or recently graduated from a degree program in Computer Science, Data Science, Software Engineering, or a related field with a focus or concentration in AI or Machine Learning.
-Technical Proficiency: Experience with NoSQL databases or other databases is desirable.
-Experience with application development or data visualization (e.g., Python, Streamlit, React, or similar frameworks).
-Familiarity with AI/LLM landscapes and an ability to analyze software costs vs. operational value (ROI).
-Ability to work independently to reverse-engineer feature sets from existing demos and build functional internal tools.
-Interest in climate solutions, regenerative aquaculture, and applying technology to biological data.
-Organized, adaptable, and proactive.
Time Commitment: 30 hours / week