ML Research Architect for Antibody Design

Abalone Bio, Inc.; United States; Hybrid; USD 172,000 - 344,000; Full time

Job summary

Abalone Bio, Inc. is seeking a talented ML Research Consultant to advance our GPCR antibody design platform. You will collaborate with the ML team to ideate, implement, and validate classifiers and generative models that translate functional activity data into next-generation biologics.

The role emphasizes rigorous ML experimentation, deep learning methods, and communication across life sciences teams. Compensation is hourly, with part-time commitment up to 10 hours/week.

Qualifications

• Bachelor’s or Master’s (5+ years) or Ph.D. in Bioinformatics, Biophysics, Computational Biology, or related field.
• Experience solving complex life sciences problems with ML or statistics.
• Strong communication in cross-functional teams.
• Understanding modern deep learning architectures and optimization fundamentals.
• 2+ years hands-on DL model development with PyTorch.
• Proficiency in Python and NumPy/Pandas/scikit-learn.
• Experience with Git and testing frameworks.
• Experience with Transformers, RNNs, or GNNs in bio/sequence data.

Responsibilities

• Evaluate sequence-function models using state-of-the-art ML to predict GPCR antibody activity.
• Implement generative models with RL or Bayesian optimization for de novo antibody design.
• Design and run rigorous ML experiments with clear hypotheses and documented outcomes.

Skills

PLLMs

Generative models

Reinforcement Learning

Bayesian Optimization

Experiment design

Python

NumPy

Pandas

scikit-learn

Git

Transformers

GNNs

RNNs

Education

Advanced degree in Bioinformatics / Computational Biology or related

Tools

PyTorch

Jupyter

Job description

Abalone Bio, Inc. is seeking a talented ML Research Consultant to advance our GPCR antibody design platform. You will collaborate with the ML team to ideate, implement, and validate classifiers and generative models that translate functional activity data into next-generation biologics.

The role emphasizes rigorous ML experimentation, deep learning methods, and communication across life sciences teams. Compensation is hourly, with part-time commitment up to 10 hours/week.