Scientist, AI/ML - Antibody DevelopabilityDatapoints Team | Ginkgo Bioworks | Boston, MA
About the RoleDatapoints, Ginkgo Bioworks' Bio × AI data generation platform, is seeking a Scientist to build and benchmark machine learning models that predict and design antibody developability. You will sit between our PROPHET-Ab high-throughput biophysical platform and the models it enables, working with both newly generated customer datasets and the GDPa public dataset series (clinical IgGs, sequence-diverse natural IgGs, bispecifics, VHH-Fcs), cross-format prediction, and generative design campaigns.
This computational role requires deep understanding of biophysical assay measurements, noise characteristics, and rigorous evaluation strategies for small-scale datasets. Ideal candidates are recent Ph.D. graduates with strong applied ML proficiency and interest in protein biophysics, motivated by integrated experimental and computational design.
Key Responsibilities- Develop and validate predictive models for developability using PLM embeddings, structural features, and physicochemical descriptors.
- Implement leakage-aware evaluation frameworks for rigorous performance assessment of small-scale datasets.
- Evaluate cross-format transferability (IgG to VHH-Fc, bispecifics) and deploy data-efficient training strategies.
- Perform rigorous QC on biophysical assay data to identify outliers and maintain high data integrity for modeling.
- Maintain and develop automated pipelines to ensure reproducibility and facilitate technical reporting.
- Disseminate findings through technical reviews, peer-reviewed manuscripts, and external scientific presentations.
QualificationsRequired- Ph.D. in Computational Biology, Bioinformatics, ML, Biophysics, or related quantitative field with emphasis on applied ML.
- Proficiency in Python and the scientific computing stack (NumPy, pandas, PyTorch/TensorFlow).
- Demonstrated experience in supervised learning on biological datasets, including expertise in cross-validation and bias mitigation.
- Knowledge of protein representations, including PLM embeddings (e.g., ESM, AbLang) and structural featurization.
- Ability to analyze biophysical data with respect to signal-to-noise ratios and experimental dynamic range.
- Effective communication across multidisciplinary teams and ability to manage concurrent technical objectives.
Preferred- Familiarity with antibody formats (VHH, scFv), therapeutic developability liabilities, and relevant characterization assays.
- Experience with state of the art supervised techniques such as tabular foundation models.
- Exposure to generative sequence modeling, diffusion models, and reward-based steering.
- Experience with protein structure prediction (AlphaFold, ABodyBuilder) and surface patch analysis.
- Prior engagement with high-throughput experimental design and collaborative data generation.
- Record of scientific publication and software engineering fundamentals (Git, testing, cloud compute).
Location: Boston, MA (Hybrid).
The base salary range for this role is $130,600 - $183,800. 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. 
