AI/ML Scientist, Antibody Developability & Design

Ginkgo Bioworks Inc.

California

On-site

USD 131,000 - 184,000

Full time

14 days+

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Benefits offered by this job

Stock awards
Comprehensive benefits
401(k) with employer contribution
Unlimited Paid Time Off

Job summary

Ginkgo Bioworks Inc. in California seeks a Scientist to build and benchmark ML models predicting antibody developability, bridging the PROPHET-Ab platform with GDPa datasets. You will work with customer data and public datasets, focusing on timely, accurate modeling and rigorous evaluation.

The role requires a PhD with applied ML skills, experience with biological data, and interest in protein biophysics. Collaboration across teams and a strong emphasis on reproducible pipelines are essential.

Qualifications

  • Ph.D. in Computational Biology, Bioinformatics, ML, Biophysics, or related field.
  • Proficiency in Python and the scientific computing stack (NumPy, pandas, PyTorch/TensorFlow).
  • Demonstrated experience in supervised learning on biological datasets, including cross-validation and bias mitigation.
  • Knowledge of protein representations, including PLM embeddings (ESM, AbLang) and structural featurization.

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 and deploy data-efficient training strategies.
  • Perform rigorous QC on biophysical assay data to identify outliers and maintain 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.

Skills

Python
NumPy
pandas
PyTorch
TensorFlow
supervised learning
data analysis

Education

PhD in Computational Biology/Bioinformatics/ML

Tools

Git
AlphaFold
ABodyBuilder

Job description

Scientist, AI/ML — Antibody Developability

California, United States

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.

Scientist, AI/ML — Antibody Developability

Datapoints Team | Ginkgo Bioworks | Boston, MA

About the Role

Datapoints, 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.
Qualifications
Required
  • 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).

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.

It is the policy of Ginkgo Bioworks to provide equal employment opportunities to all employees, employment applicants, and EOE disability/vet.

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I 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.

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For government reporting purposes, we ask candidates to respond to the below self-identification survey.Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in aconfidential file.

As set forth in Ginkgo Bioworks Inc.’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

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