ML Engineer: Antibody & Biologics Modeling

Apheris; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Apheris is seeking an ML Engineer to advance our large molecule ML programs in antibody modeling, co-folding and developability. You will translate research prototypes into production-ready models that run in federated pharma data environments.

Join a hands-on team at the intersection of biology and foundation models, tackling drug discovery challenges with scalable ML, rigorous evaluation, and cross-functional collaboration.

Qualifications

• MSc or PhD in ML, computational biology, bioinformatics, physics or related field.
• Strong Python and PyTorch, with hands-on DL model training on biomolecular data.
• Experience with co-folding models or protein language models beyond inference.

Responsibilities

• Build, fine-tune and extend large biomolecular models for antibody modeling and developability.
• Turn research code into reliable components for federated training pipelines.
• Design evaluations and benchmarks; deliver results packages for partners.
• Own workstreams through release milestones; identify risks and trade-offs early.
• Collaborate with product, engineering, research and consortium members to meet application needs.

Skills

Python

PyTorch

Biomolecular DL

Model evaluation

Education

MSc/PhD in ML or Computational Biology

Tools

OpenFold

AlphaFold

Boltz/ESM

Kubernetes

Federated learning

Job description

Apheris is seeking an ML Engineer to advance our large molecule ML programs in antibody modeling, co-folding and developability. You will translate research prototypes into production-ready models that run in federated pharma data environments.

Join a hands-on team at the intersection of biology and foundation models, tackling drug discovery challenges with scalable ML, rigorous evaluation, and cross-functional collaboration.