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Salary: USD 115,000 - 165,000 / annual
Ginkgo Datapoints, a business unit within Ginkgo Bioworks, is building AI-backed biotechnology capabilities for drug discovery and development. The Small Molecules team seeks a Senior Engineer I, Computational Synthetic Chemist to design and execute multi-step syntheses of novel drug-like molecules, including singleton analogs and small focused sets that cannot be made in plate format.
You will own route selection, execution, purification, and characterization end-to-end. Computational route planning, retrosynthesis, condition prediction, and automated or high-throughput experimentation resources will be standard working tools—not occasional aids. You will consume model output, judge when it is useful, correct it when it is not, and feed outcomes back into the planning and prediction workflows.
Key responsibilities include:
**Multi-step synthesis and compound delivery:** Design, select, and execute practical multi-step routes to novel drug-like singleton compounds and focused sets under real constraints on time, materials, building blocks, and available resources. Apply a broad synthetic-organic chemistry toolkit and own purification and characterization through delivery of high-quality, well-characterized compounds on schedule.
**Computationally enabled chemistry:** Use computer-aided synthesis planning, retrosynthesis, and reaction-condition tools routinely; critically evaluate proposed routes and predictions and explain when they are implausible, impractical, or outside reliable coverage. Use chemical structure and reaction representations and building-block catalogs to constrain plans to realistic starting materials, and design or interpret HTE and other reaction-optimization experiments. Feed practical outcomes and corrected synthetic judgment back into planning, prediction, and cheminformatics workflows.
**Data, automation, and collaboration:** Record every campaign, including failures, in structured, machine-readable form covering conditions, stoichiometry, outcomes, analytical data, and negative results. Design chemistry for automation and parallel execution where useful, while recognizing when a route genuinely requires manual bench work. Collaborate with chemists, computational scientists, and software engineers to define useful tools, make go/no-go heuristics explicit, and mentor junior chemists.
The ideal candidate is an accomplished bench chemist who is also fluent in computer-aided synthesis planning (CASP), reaction-prediction tools, and reaction data. You will be the resident synthetic-chemistry judgment for this part of the design–make–test loop and will mentor junior chemists using the same tools. This is not a software or ML research position; it is a chemistry role for someone who wants to make computational workflows genuinely useful in practice.
**Requirements:**
- Ph.D. in synthetic organic chemistry, medicinal chemistry, or a closely related field, plus 3 years of relevant industry or postdoctoral experience; or an M.S. with 6 years, or a B.S. with 9 years, of relevant experience.
- Demonstrated ability to design and execute multi-step syntheses, including routes of approximately five or more steps through characterized final compounds, and to deliver compounds on schedule.
- Independent route-design judgment under real constraints on materials, time, building blocks, and execution resources, supported by a broad synthetic-organic reaction toolkit and strong purification and characterization skills.
- Routine hands-on use of computer-aided synthesis planning or retrosynthesis tools, with the judgment to recognize when a proposed route or prediction should not be trusted.
- Fluency with chemical structure and reaction data, including molecular and reaction representations, compound registration, stereochemistry, salts, tautomers, and building-block catalogs.
- Experience with reaction screening, HTE, design of experiments, or related optimization workflows, plus disciplined structured capture of conditions, outcomes, analytical results, and failures.
**Preferred qualifications:** Python scripting with tools such as RDKit, pandas, or Jupyter for manipulating compound sets, parsing analytical output, or prototyping analyses. Experience running chemistry on robotic platforms, liquid handlers, flow systems, or other automated resources. Industrial HTE or nanoscale reaction-screening experience. Prior work in a CRO, fee-for-service, or similarly schedule-driven environment. Experience with ELN/LIMS configuration or reaction-data model definition. Experience scaling a validated route from milligram to multi-gram quantities. Experience with inline or process monitoring such as ReactIR, benchtop NMR, or online LC-MS. Experience mentoring or supervising junior chemists. Publications or patents describing multi-step routes to biologically active compounds.
