Computational Synthetic Chemist

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.

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.

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.

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.

You understand that computational models capture the current state of knowledge: they will never be perfect, but they can support learning and better decisions. You know the difference between useful guidance and an output that is not reliable enough to use.

You balance skepticism with practical progress. You make thoughtful go/no-go calls, state the limits of your judgment, and route unresolved questions to the right person or experiment rather than resolving them by assertion.

You are intellectually curious and impatient with the status quo, with a passion for establishing and advancing state-of-the-art chemistry workflows in practical production settings.

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.

Help build the world’s most computationally enabled synthesis capability, combining expert chemistry with route planning, reaction prediction, automation, and learning.

Help connect route design, reaction prediction, synthesis, testing, and learning across Ginkgo’s automated platforms.

Develop workflows to capture, structure, and learn from the reaction data generated by autonomous laboratory systems.

Join a technically ambitious, cross-functional team building the computational foundations for AI-enabled drug discovery.

Receive competitive compensation, generous equity in a public company, and a robust benefits package.

The base salary range for this role is $115,000–$165,000. Actual pay within this range will depend on a candidate's skills, expertise, and experience. We also offer company stock awards, a comprehensive benefits package including medical, dental & vision coverage, health spending accounts, voluntary benefits, leave of absence policies, 401(k) program with employer contribution, 8 paid holidays in addition to a full-week winter shutdown and unlimited Paid Time Off policy.

Ginkgo has implemented a return to office policy effective October 1, 2025 with required in office days 5x per week. This policy applies to all employees who live within 50 miles of Ginkgo’s offices in Boston, MA, Emeryville, CA and West Sacramento, CA.