> Markdown version of [/jobs/ext/2720603-senior-engineer-iii-adme](https://www.wearedevelopers.com/jobs/ext/2720603-senior-engineer-iii-adme). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Engineer III, ADME - **Company:** Ginkgo Bioworks - **Location:** Boston, MA, United States - **Experience:** Expert - **Salary:** $185,000.0 - $278,800.0 - **Contract:** Permanent contract - **Skills:** Computer Programming, Data Visualization, R (Programming Language), Python (Programming Language), Automation of Marketing, Spotfire - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/senior-engineer-iii-adme-ginkgo-bioworks-inc-7737624 ## About the Role Here at Ginkgo, we are aiming to modernize ADME by bringing our experience in high-throughput screening to the in vitro small molecule drug pipeline. We are re-imagining ADME at scale, and we are seeking a visionary and technically adept High-Throughput ADME Scientist to help us build and execute this next-generation platform. This role is critical in accelerating our drug discovery pipeline by providing timely and high-quality in vitro ADME (Absorption, Distribution, Metabolism, and Excretion) data to guide lead optimization. The ideal candidate will possess deep technical expertise in developing, validating, and implementing a variety of high-throughput ADME assays., * Education: Ph.D. in Pharmaceutical Sciences, Pharmacology, Analytical Chemistry, or a related field with 7+ years of relevant industry experience, or a Master's degree with 12+ years of industry experience. * Technical Expertise: * Extensive, hands-on experience with LC-MS or acoustic MS particularly in a high-throughput setting. * Proven track record in developing and running automated in vitro ADME assays using state-of-the-art laboratory automation. * Strong theoretical and practical knowledge of drug metabolism pathways and DMPK. * Familiarity with common ADME prediction software and data visualization tools. Preferred Skills * + Experience using lab automation. + Programmatic coding experience (e.g., Python, R, or similar). + Data visualization (Spotfire, Python, R, or similar). ## Description Assay Development & Implementation * Design, develop, optimize, and validate a wide array of high-throughput in vitro ADME assays (e.g., solubility, MDCK permeability, plasma protein binding, microsomal stability, hepatocyte stability, and CYP inhibition/induction). * Automation and Screening: Experience working with automated liquid handlers such as Hamilton, Lynx, Bravo, and Formulatrix. Data Analysis & Reporting * Develop and perform mass spectrometry (LC-MS/MS, acoustic ejection mass spectrometry, or similar) analysis of samples from ADME assays. Responsibilities will include method development and troubleshooting. * Ensure proper sample preparation and management for high-throughput analysis. * Analyze, interpret, and report complex ADME data, including calculating key pharmacokinetic parameters. * Present results and provide expert recommendations to medicinal chemists and project teams to inform go/no-go decisions. Quality & Compliance * Maintain detailed and accurate laboratory records, SOPs, and electronic notebooks. * Ensure all laboratory activities comply with internal quality standards and safety regulations. Operational ownership & risk management * Lead day-to-day operations of the ADME team * Build and maintain "buttoned-up" SOPs, runbooks, checklists, and QC dashboards for all established assays. Cross-functional partnership * Collaborate with computational and data teams on metadata schemas, QC metrics, and analysis-ready outputs. * Work closely with program leads to scope work, set expectations, and communicate progress and risks. * Contribute to portfolio and capacity planning, including scenarios for large campaigns. Leadership, mentoring, and training * Provide technical leadership and day-to-day guidance for scientists on ADME workflows. * Contribute to the Datapoints skill matrix by defining training levels, shadowing plans, and up-leveling team members on key assays * Document methods, "tips & tricks", and troubleshooting guides; lead trainings and onboarding sessions. ## Related Videos - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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