Senior/Principal Scientist (AI for Protein Engineering)

TL;DR

Senior/Principal Scientist (AI for Protein Engineering): Developing generative and predictive models to drive biomolecule design programs with an accent on antibody engineering and wet-lab validation. Focus on creating end-to-end design workflows, adapting SOTA AI methods, and building active learning loops to refine model performance.

Location: Cambridge, MA USA

Salary: $268,000 - $358,000 USD

Company

hirify.global is building an autonomous AI-driven platform to accelerate scientific discovery across medicine, materials, and energy.

What you will do

• Develop and own protein design and engineering workflows for antibody campaigns, including de novo design and affinity maturation.
• Translate campaign requirements into well-defined ML problems and design specifications.
• Adapt and extend state-of-the-art AI methods, such as generative models and protein language models, for biomolecule engineering.
• Partner with Life Science Research teams to build active learning loops where wet-lab data improves model performance.
• Expand the protein engineering platform to additional modalities like enzymes and peptides.

Requirements

• PhD in Computational Biology, Computer Science, Machine Learning, Biophysics, or a related quantitative field.
• Proven track record of successful design of wet-lab-validated biomolecules through AI.
• Deep ML expertise with the ability to modify and adapt SOTA AI approaches for protein engineering.
• Strong fluency across both ML and protein biology, specifically antibody design.
• Ability to drive a research and engineering program independently from definition to validation.

Nice to have

• Direct experience designing antibodies, nanobodies, or therapeutic proteins for clinical pipelines.
• Experience with structure prediction, generative protein design (diffusion, flow-matching), and protein language models.
• Expertise in structural biology and conformational dynamics.
• High-impact publications or open-source contributions in AI for Science (e.g., Nature, NeurIPS, ICML).

Culture & Benefits

• Competitive base compensation with bonus potential.
• Generous early-stage equity.
• Comprehensive U.S. and International benefits packages.
• High-velocity startup environment guided by truth, trust, curiosity, and grit.