Teams at GenBio AI

Conduct AI research for molecular and biological design within GenBio AI’s Virtual Cell World Model. Develop, implement, and debug deep learning models using frameworks such as JAX, TensorFlow, or PyTorch, with potential applications in generative modeling, graph neural networks, protein structure prediction, molecular design, and distributed training. Collaborate across AI and biology while operating independently in an interdisciplinary startup environment.

Leads engineering execution for AI-driven computational biology systems, translating research into scalable production platforms. Responsibilities include setting roadmaps and delivery timelines, contributing code, architecting AI infrastructure, operationalizing foundation models, enforcing testing and CI/CD standards, mentoring engineering teams, and coordinating with executives and research leaders. The role requires deep expertise in generative AI infrastructure, GPU clusters, distributed systems, and production deployment, with computational biology and startup experience preferred.

Build the user-facing software platform for a programmable Virtual Cell, including scalable backend services, APIs, distributed systems, biological simulations, experiment workflows, and multimodal data processing. Integrate AI and machine learning inference into reliable scientific products, improve platform performance and reliability, and collaborate with engineering, research, and scientific product teams.