Ginkgo Bioworks
Scientist, AI/ML — Antibody Developability
$131K–$184K
California, United States +1 · Full-time · Posted Sep 2, 2026
- Location
- California, United States
Boston, Massachusetts, United States - Experience
- No specific number of years stated; ideal candidates are recent Ph.D. graduates.
- Education
- Ph.D. in Computational Biology, Bioinformatics, ML, Biophysics, or related quantitative field.
About the job
Build and benchmark machine learning models to predict and design antibody developability, integrating biophysical assay data with computational methods.
What you'll do
- Develop predictive models and leakage-aware evaluation strategies for small biological datasets, including cross-format transfer.
- Perform quality control on biophysical assay data and maintain reproducible automated pipelines.
- Report and disseminate findings through technical reviews, manuscripts, and scientific presentations.
What they ask for
- Ph.D. in Computational Biology, Bioinformatics, ML, Biophysics, or a related quantitative field, with emphasis on applied ML.
- Proficiency in Python and scientific computing tools, including NumPy, pandas, and PyTorch/TensorFlow.
- Experience applying supervised learning to biological datasets, including cross-validation and bias mitigation.
- Knowledge of protein representations, PLM embeddings, structural featurization, and analysis of biophysical data.
Nice to have
- Familiarity with antibody formats, therapeutic developability liabilities, and characterization assays.
- Experience with generative sequence modeling, diffusion models, reward-based steering, or protein structure prediction.
Pay
USD 130,600 – USD 183,800 base salary
Tools
Python, NumPy, pandas, PyTorch/TensorFlow, PLM embeddings, ESM, AbLang, AlphaFold
AI focus
Develop and benchmark machine learning models to predict and design antibody developability, including cross-format transfer and generative design campaigns.
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