
Biographica helps agricultural and biotech teams find genes to edit faster, reducing time and failure in crop trait development. It uses graph-based machine learning and genomics to model biological relationships and predict target genes, combining in silico prioritization with in vivo experimental validation. The company operates as a B2B biotechnology platform that partners with crop companies and research labs and provides developer-friendly interfaces and collaboration workflows. Biographica targets translational crop improvement and precision gene-editing programs to accelerate trait discovery across diverse crops.

Biographica helps agricultural and biotech teams find genes to edit faster, reducing time and failure in crop trait development. It uses graph-based machine learning and genomics to model biological relationships and predict target genes, combining in silico prioritization with in vivo experimental validation. The company operates as a B2B biotechnology platform that partners with crop companies and research labs and provides developer-friendly interfaces and collaboration workflows. Biographica targets translational crop improvement and precision gene-editing programs to accelerate trait discovery across diverse crops.
About Us 🌽 Safeguarding the future of food
Biographica is on a mission to accelerate the development of more productive, sustainable, nutritious & climate-resilient food sources. To achieve this, we're building the world’s first ML-driven target discovery platform for crop gene-editing.
🧬 Target discovery for gene-editing
While gene-editing of crops is becoming ever more efficient, identifying which genes to edit and how remains a significant challenge. To overcome this bottleneck, we use cutting-edge deep learning to accurately and efficiently identify high value genetic targets for crop gene-editing. Our approach draws inspiration from advancements in the drug discovery space, incorporating transformers, graphs & causal-ML to build a best-in-class discovery platform for plant sciences.
🤖 Building agent-native scientist-in-the-loop discovery
Our next chapter is to productise target discovery so we can deliver deep, traceable discovery projects quickly and in parallel. We believe scientific agents, grounded in Biographica-curated data and proprietary models, will be key to scaling both the breadth and depth of our analyses. This role will own the orchestration and platform layer that makes agentic workflows reliable, reproducible, and genuinely useful to scientists.
👥 Team
Led by co-founders Dom (CTO) and Cecy (CEO), we are now a team of 13, including 2 ML engineers, 2 data engineers, 3 bioinformaticians & 2 experimental scientists. We primarily work together in person from our office in Spitalfields, London, 4 days per week. This role will be based in London, with close collaboration across ML, data and scientific product.
What we're looking for
We’re hiring an agentic-focused software engineer to build out internal agentic frameworks for our discovery product. You will define and implement the operating system that allows scientists to run repeatable, agent-in-the-loop tool-using workflows while maintaining provenance, traceability and checkpoints.
Your First Priorities Will Be
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