Our mission is to make biology easier to engineer. Ginkgo is constructing, editing, and redesigning the living world in order to answer the globe’s growing challenges in health, energy, food, materials, and more. Our bioengineers make use of an in-house automated foundry for designing and building new organisms. 

Senior Engineer I, Cheminformatics & Synthesis Prediction

Boston, Massachusetts

About Ginkgo Datapoints

Ginkgo Datapoints, a business unit within Ginkgo Bioworks, is ushering in the coming era of AI-backed biotechnology breakthroughs. By leveraging Ginkgo’s automation and digital infrastructure, Datapoints builds high-quality, large-scale datasets and technical capabilities that accelerate drug discovery and development.

The Small Molecules team is looking for a cheminformatics scientist to support the computational work of building and navigating makeable chemical spaces. This includes building the space itself, developing tools that help scientists search and use it, and predicting the outcomes of chemical reactions that connect design to synthesis.

Role Overview

We are hiring a Senior Engineer I, Cheminformatics to develop and operate the cheminformatics workflows behind Ginkgo’s makeable chemical space and reaction-prediction capabilities.

This is a hands-on production role spanning two connected areas: building and maintaining large makeable chemical spaces through reaction enumeration, and integrating, evaluating, and improving reaction-prediction workflows such as retrosynthesis and reaction-condition prediction. You will work with reaction templates, molecular representations, functional-group logic, vendor building blocks, predictive models, and reaction data that feeds the design–make–test loop.

The ideal candidate combines practical cheminformatics engineering, experience with reaction prediction, and strong chemistry fluency. Internal chemists provide deep synthetic and medicinal chemistry expertise; your role is to translate their questions into reliable computational workflows and explain what the systems did and why. This is not an ML research position. We prefer to adopt or adapt published methods and open-source tools before building new systems.

Key Responsibilities

Makeable chemical space

• Develop and improve reaction-enumeration workflows, including reaction SMARTS templates, functional-group gating, building-block curation, and production runs.