Principal Scientist - Protein MIL

Commonwealth Sciences, Inc.; Boston (MA); On-site; USD 180,000 - 250,000; Full time

Job summary

Commonwealth Sciences, Inc. seeks a senior leader to drive computational biology and ML efforts for protein discovery and design. You will develop and benchmark models for structure prediction, protein properties, and antibody design, while building scalable data pipelines and tools for researchers.

The role collaborates with experimental teams, mentors a small group, and shapes data management and MLOps practices across projects.

Qualifications

• PhD in computational biology, bioinformatics, biophysics, machine learning, or a related field.
• 5+ years of relevant industry or research experience, including technical leadership or mentoring/managing computational scientists.
• Strong Python programming skills and hands-on experience with deep learning frameworks such as PyTorch.
• Demonstrated experience developing, modifying, training, or applying ML models for protein structure prediction and/or protein design.

Responsibilities

• Lead computational biology and machine learning efforts supporting protein discovery, engineering, and characterization.
• Develop, fine-tune, and benchmark deep learning and foundation models for protein structure prediction, protein design, and antibody/binder discovery.
• Build predictive models for protein properties including stability, aggregation, expression, binding affinity, and developability.
• Design and execute computational protein and antibody design campaigns and integrate results with experimental validation cycles.
• Develop scalable computational pipelines for antibody discovery, protein characterization, sequencing, proteomics, and other biological datasets.
• Build data platforms, databases, APIs, and visualization tools that enable researchers to efficiently access and utilize complex biological data.
• Collaborate with experimental scientists to design studies, analyze results, and integrate computational approaches into laboratory workflows.
• Manage cloud, GPU, and high-performance computing environments supporting machine learning and large-scale biological analysis.
• Lead, mentor, and develop a small team of computational biologists and bioinformaticians.
• Establish best practices for data management, reproducibility, version control, model deployment, and MLOps.
• Communicate computational strategies and findings to both technical and non-technical audiences and contribute to publications, intellectual property, and product development.

Skills

Python

PyTorch

Leadership

Mentoring

Education

PhD in computational biology or related field

Tools

GPU HPC

Cloud platforms

Job description

• Lead computational biology and machine learning efforts supporting protein discovery, engineering, and characterization.
• Develop, fine-tune, and benchmark deep learning and foundation models for protein structure prediction, protein design, and antibody/binder discovery.
• Build predictive models for protein properties including stability, aggregation, expression, binding affinity, and developability.
• Design and execute computational protein and antibody design campaigns and integrate results with experimental validation cycles.
• Develop scalable computational pipelines for antibody discovery, protein characterization, sequencing, proteomics, and other biological datasets.
• Build data platforms, databases, APIs, and visualization tools that enable researchers to efficiently access and utilize complex biological data.
• Collaborate with experimental scientists to design studies, analyze results, and integrate computational approaches into laboratory workflows.
• Manage cloud, GPU, and high-performance computing environments supporting machine learning and large-scale biological analysis.
• Lead, mentor, and develop a small team of computational biologists and bioinformaticians.
• Establish best practices for data management, reproducibility, version control, model deployment, and MLOps.
• Communicate computational strategies and findings to both technical and non-technical audiences and contribute to publications, intellectual property, and product development.

Requirements

• PhD in computational biology, bioinformatics, biophysics, machine learning, or a related field, with strong experience in protein science or biochemistry.
• 5+ years of relevant industry or research experience, including technical leadership or experience mentoring/managing computational scientists.
• Strong Python programming skills and hands-on experience with deep learning frameworks such as PyTorch.
• Demonstrated experience developing, modifying, training, or applying machine learning models for protein structure prediction and/or protein design.
• Experience working with multimodal biological datasets, including sequence, structure, assay, sequencing, or proteomics data.
• Proven experience with de novo protein, binder, or antibody design and experimental validation.
• Strong understanding of computational protein science and the ability to translate research methods into practical tools and workflows.