Jobs at Generate Biomedicines

This role will own the continued excellence of conventional protein analytics, developability, and protein-protein interaction technologies while building the next generation of at-scale experimental systems. The ideal candidate brings deep technical breadth, a quantitative mindset, and a clear point of view on how pooled assays, DNA/barcode-enabled readouts, synthetic biology, automation, microfluidics, advanced detection, and computational modeling can transform how protein therapeutics are evaluated.

• Set and drive the multi-year scientific and organizational vision for Protein Analytics & Biophysics, aligning functional strategy with Generate's platform, portfolio, and company priorities.
• Define the next generation of biophysical, biochemical, developability, and protein-protein interaction measurement capabilities for protein therapeutics, with a particular focus on miniaturized, pooled, high-throughput, and nanoscale approaches.
• Lead the continued evolution of conventional analytical and interaction workflows, including HPLC/UPLC, LC/MS, electrophoretic, thermal stability, light scattering, plate-based, and biosensor-based platforms, ensuring rigor, reproducibility, and decision relevance.
• Build a strategy that connects conventional analytical and biosensor technologies with emerging pooled or massively multiplexed approaches, enabling Generate to measure protein attributes at scales that match the output of generative design.
• Partner with Prototyping, Technology, Automation, Data Sciences, Machine Learning, Protein Sciences, Biology, and CMC/Tech Ops to design, operationalize, validate, and scale new assay concepts into production-quality capabilities.
• Identify, evaluate, and implement external and internal technologies that can unlock smaller sample volumes, richer attribute profiles, higher throughput, improved sensitivity, or new classes of protein interaction and developability data.
• Establish data standards, quality expectations, assay controls, and analytical frameworks that allow high-throughput measurements to be used confidently for model training, candidate triage, and program decision-making.
• Ensure the function generates high-quality, decision-enabling data across Discovery, Candidate Selection, and early Development, including developability, stability, specificity, affinity, kinetics, and manufacturability-relevant attributes.

• Ph.D. in Biophysics, Biochemistry, Molecular Biology, Chemical Biology, Bioengineering, Synthetic Biology, Protein Engineering, or a related scientific discipline; or equivalent depth of industry experience.
• 12+ years experience in biopharma, biotechnology, synthetic biology, protein engineering, or a related field, with substantial leadership experience in protein analytics, biophysics, developability, and protein-protein interaction characterization. 
• Significant progressive experience in biopharma, biotechnology, synthetic biology, protein engineering, or a related field, with substantial leadership experience in protein analytics, biophysics, developability, and protein-protein interaction characterization.
• A track record of building, inventing, or scaling novel assay platforms for protein therapeutics, especially miniaturized, pooled, multiplexed, microfluidic, barcode-enabled, sequencing-enabled, cell-based, or nanoscale biophysical or biochemical measurements.
• Demonstrated ability to move beyond single-sample, low-throughput paradigms and create experimental systems that generate high-dimensional, quantitative data at the scale needed for AI/ML-enabled protein design.
• Deep technical expertise across conventional analytical and biophysical methods, such as HPLC/UPLC (SEC, RP, HIC, IEX), LC/MS, CE-SDS, cIEF, DSF, DSC, DLS, SEC-MALS, SPR, BLI, and related technologies.
• Strong understanding of protein-protein interaction measurement, including affinity, kinetics, specificity, cross-reactivity, epitope/binning, avidity, and context-dependent binding behavior.
• Strong quantitative mindset and experience using data quality, assay statistics, modeling, and informatics to shape scientific strategy, technology investment, and operational decision-making.
• Experience partnering closely with prototyping, automation, engineering, computational, and technology teams to translate exploratory assay concepts into robust, reproducible, and scalable capabilities.
• Demonstrated success as a senior people leader, including leading leaders, developing senior scientific talent, and scaling high-performing teams through periods of change.
• Exceptional collaboration and communication skills, with a clear track record of influencing across complex, matrixed organizations and engaging executive stakeholders with clarity, candor, and credibility.
• Experience advancing biologics programs across Discovery and early Development, with an understanding of developability considerations, candidate selection, and downstream impact.