Cheminformatics & Synthesis Prediction
Ginkgo Bioworks · Boston, Massachusetts
About this role
**Senior Engineer I, Cheminformatics & Synthesis Prediction** **About Ginkgo Datapoints** Ginkgo Datapoints (a business unit within Ginkgo Bioworks) is building AI-backed biotechnology breakthroughs. Using Ginkgo’s automation and digital infrastructure, Datapoints creates 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 computational work for building and navigating makeable chemical spaces—plus predicting reaction outcomes that connect design to synthesis. --- ## Role Overview You’ll develop and operate cheminformatics workflows behind Ginkgo’s **makeable chemical space** and **reaction-prediction** capabilities. This is a hands-on production role across two connected areas: - **Build & maintain large makeable chemical spaces** via reaction enumeration - **Integrate, evaluate, and improve reaction-prediction workflows** (e.g., retrosynthesis and reaction-condition prediction) You’ll work with reaction templates, molecular representations, functional-group logic, vendor building blocks, predictive models, and reaction data that feeds the design–make–test loop. *Note: This is not an ML research position. The team prefers adopting/adapting published methods and open-source tools before building new systems.* --- ## Key Responsibilities ### Makeable chemical space - Develop and improve **reaction-enumeration workflows** (reaction SMARTS templates, functional-group gating, building-block curation, production runs) - Work with **large vendor catalogs**, balancing coverage, price, availability, lead time, and data quality - Improve handling of **regioisomers, stereochemistry, resolution limits**, and other ambiguity sources - Build reliable workflows for **structure handling, reaction execution, sanitization, identifiers, SDF files, and metadata** ### Reaction prediction & design–make–test workflows - Integrate and evaluate approaches for **retrosynthesis**, **synthetic success**, **reaction-condition prediction**, and related reaction modeling tasks - Assess models/workflows for **calibration, coverage, applicability domain**, and practical usefulness—surface uncertainty and risk flags - Connect predicted reactions and enumerated compounds to **experimental design** and downstream learning - Consolidate reaction data (conditions, yields, failed reactions, provenance) into a **shared, machine-readable source** to support future model improvement ### Production platform & collaboration - Write maintainable code and contribute to **service-oriented systems**, deployment workflows, and data pipelines - Partner with internal chemists and cross-functional teams to translate scientific questions into reliable computational workflows - Scope and review external/consultant work with clear specifications and acceptance criteria - Work on commercial digital products by integrating pricing/ordering data and deploying/maintaining related services and tools - Design/build/optimize **Model Context Protocols (MCPs)** and agentic frameworks to support LLM-based work and integrate cheminformatics tools into automated workflows --- ## Minimum Qualifications - **Ph.D.** in cheminformatics, computational chemistry, organic chemistry, medicinal chemistry, or a closely related quantitative field **+ 3 years** relevant industry/postdoc experience; or **M.S. + 6 years**; or **B.S. + 9 years** - Strong practical expe
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