{"id":3121185,"url":"https://alion.io/job/ginkgo-bioworks-cheminformatics-synthesis-prediction","title":"Cheminformatics & Synthesis Prediction","company":{"id":58589,"name":"Ginkgo Bioworks","domain":"ginkgo.bio","url":"https://alion.io/company/ginkgo-bioworks","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"C","score":65,"open_postings":19,"ghost_share":0.579,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-28T05:59:10Z"}},"role":"Biotech","role_family":"Biotech","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Boston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":112000,"max_usd":212000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":27},"experience_years_min":9,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Docker","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"LIMS","optional":true}],"status":"live","first_seen_at":"2026-08-25T14:13:08Z","employer_posted_date":"2026-08-25","last_verified_at":"2026-10-28T12:18:23Z","board_verified":true,"closed_at":null,"days_open":64,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":63},"description":"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. \nSenior Engineer I, Cheminformatics & Synthesis Prediction\nBoston, Massachusetts\nAbout Ginkgo Datapoints\nGinkgo 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.\nThe 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.\nRole Overview\nWe are hiring a Senior Engineer I, Cheminformatics to develop and operate the cheminformatics workflows behind Ginkgo’s makeable chemical space and reaction-prediction capabilities.\nThis 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.\nThe 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.\nKey Responsibilities\nMakeable chemical space\nDevelop and improve reaction-enumeration workflows, including reaction SMARTS templates, functional-group gating, building-block curation, and production runs.\n\nWork with large vendor catalogs while balancing chemical coverage, price, availability, lead time, and data quality.\n\nImprove treatment of regioisomers, stereochemistry, resolution limits, and other sources of ambiguity in enumerated chemical space.\n\nBuild reliable workflows for structure handling, reaction execution, sanitization, identifiers, SDF files, and metadata.\n\nReaction prediction and design-make-test workflows\nIntegrate and evaluate approaches for retrosynthesis, synthetic success, reaction-condition prediction, and related reaction modeling tasks.\n\nAssess models and workflows for calibration, coverage, applicability domain, and practical usefulness; surface uncertainty and risk flags rather than bare point estimates.\n\nHelp connect predicted reactions and enumerated compounds to experimental design, make-test workflows, and downstream learning.\n\nConsolidate reaction data-including conditions, yields, failed reactions, and provenance-into a shared, machine-readable source that supports future model improvement.\n\nProduction platform and collaboration\nWrite maintainable code and contribute to service-oriented systems, deployment workflows, and data pipelines.\n\nPartner with internal chemists and cross-functional teams to translate scientific questions into reliable computational workflows and interpret results.\n\nScope and review external or consultant work with clear specifications and acceptance criteria.\n\nWork on commercial digital products by integrating pricing and ordering data and functionalities, and deploying and maintaining related services and tools.\n\nDesign, build, and optimize Model Context Protocols (MCPs) and agentic frameworks to support LLM-based work and integrate cheminformatics tools into automated workflows.\n\nMinimum Qualifications\nPh.D. in cheminformatics, computational chemistry, organic chemistry, medicinal chemistry, or a closely related quantitative 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.\n\nStrong practical experience in cheminformatics and reaction prediction, including experience with retrosynthesis, reaction-condition prediction, synthetic accessibility, or related workflows.\n\nExperience working with reaction SMARTS, functional-group classification, molecular representations, and chemical structure data.\n\nProduction experience with RDKit or an equivalent cheminformatics toolkit.\n\nExperience working with large chemical or vendor building-block catalogs and understanding the trade-offs involved in coverage, scale, and data quality.\n\nStrong Python skills and experience writing code that others can run and maintain.\n\nFamiliarity with service-oriented software, Docker, environment-based configuration, and data pipelines.\n\nWorking knowledge of common medicinal-chemistry synthetic transformations and the ability to collaborate effectively with synthetic chemists.\n\nClear technical communication skills and a disciplined approach to documentation, provenance, and reproducibility.\n\nWorking Style\nYou understand that models are mathematical representations of the current state of knowledge: they will never be perfect, but they can support learning and better decisions. You know how to distinguish useful signal from an output that is not reliable enough to use, and communicate uncertainty and limitations clearly.\n\nYou balance scientific rigor with practical progress. You make thoughtful trade-offs, avoid overclaiming, and collaborate clearly with chemists and engineers to turn imperfect computational tools into useful workflows.\n\nYou are intellectually curious and impatient with the status quo, with a passion for establishing and advancing state-of-the-art computational methods in practical production settings.\n\nPreferred Qualifications\nExperience with large makeable or synthesizable chemical spaces, whether commercial or in-house.\n\nExperience operating a combinatorial library-enumeration pipeline or reaction-prediction workflow in production.\n\nExperience evaluating predictive models, including uncertainty estimation, calibration, applicability domain, or ranked candidate generation.\n\nExperience with regiochemistry, stereochemistry, chemical registration systems, ELN/LIMS integration, or chemical data standards.\n\nExperience connecting computational design to wet-lab results in a design-make-test-learn environment.\n\nContributions to open-source cheminformatics or experience evaluating third-party chemistry platforms.\n\nExperience building and optimizing Model Context Protocols (MCPs), agentic frameworks, or integrating cheminformatics tools with LLM-based workflows.\n\nWhy Join Ginkgo Datapoints?\nBuild cheminformatics technology and workflows on Nebula, the world’s largest autonomous laboratory.\n\nHelp connect molecular design, reaction prediction, synthesis, testing, and learning across Ginkgo’s automated platforms.\n\nDevelop workflows to ingest, structure, and learn from the high-quality data generated by autonomous laboratory systems.\n\nJoin a technically ambitious, cross-functional team building the computational foundations for AI-enabled drug discovery.\n\nReceive competitive compensation, generous equity in a public company, and a robust benefits package.\n\nThe base salary range for this role is $115,00-165,000. 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.\nGinkgo 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.\nIt is the policy of Ginkgo Bioworks to provide equal employment opportunities to all employees, employment applicants, and EOE disability/vet. \nPrivacy Notice\nI understand that I am applying for employment with Ginkgo Bioworks and am being asked to provide information in connection with my application. I further understand that Ginkgo gathers this information through a third-party service provider and that Ginkgo may also use other service providers to assist in the application process. Ginkgo may share my information with such third-party service providers in connection with my application and for the start of employment. Ginkgo will treat my information in accordance with Ginkgo's Privacy Policy. By submitting this job application, I am acknowledging that I have reviewed and agree to Ginkgo's Privacy Policy as well as the privacy policies of the third-party service providers used by Ginkgo's associated with the application process.","description_format":"text","description_chars":9364,"description_truncated":false,"requirements":{"experience_years_min":9,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"Massachusetts","iso":null,"kind":"city"},{"name":"California","iso":null,"kind":"city"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Bioinformatics","Biotechnology","Science & Engineering","Biomedical Engineering"],"lifecycle":[{"event":"open","at":"2026-10-23T00:29:32Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 6","filings_12m":6,"filings_prev_12m":14,"green_card_filings_12m":0,"median_offered_wage_usd":117500,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":0}],"liveness":{"score":20,"band":"cold","label":"Long shot","p_open":1,"p_active":0.458,"p_room":0.44,"age_days":63,"expected_fill_days":45,"reasons":["conf:3","stale_co","win:tail","crowd:"],"computed_at":"2026-10-28T05:59:10Z"},"pay":null,"html_url":"https://alion.io/job/ginkgo-bioworks-cheminformatics-synthesis-prediction","json_url":"https://alion.io/job/ginkgo-bioworks-cheminformatics-synthesis-prediction.json","meta":{"generated_at":"2026-10-28T16:27:33Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":22342,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-29T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":58589},"rest":"https://alion.io/mcp/rest/get_company?id=58589"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fginkgo-bioworks-cheminformatics-synthesis-prediction"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fginkgo-bioworks-cheminformatics-synthesis-prediction"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fginkgo-bioworks-cheminformatics-synthesis-prediction"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/ginkgo-bioworks-cheminformatics-synthesis-prediction\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fginkgo-bioworks-cheminformatics-synthesis-prediction"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3121185}},{"tool":"search_jobs","arguments":{"company":"ginkgo.bio","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3121185},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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