Principal BioML Scientist (AI)

TL;DR

Principal BioML Scientist (AI): Building and leading the applied science footprint for an autonomous-science platform with an accent on target identification and translational BioML. Focus on co-architecting the AI-for-Cell-Biology scientific direction and integrating AI with lab automation to accelerate therapeutic discovery.

Location: San Francisco, CA, USA

Salary: $171,600 - $270,600 USD

Company

hirify.global is building Scientific Superintelligence to solve medicine's hardest problems via an autonomous operating system for science that executes the scientific method independently.

What you will do

• Lead and grow the applied science footprint, recruiting and mentoring a team of domain-embedded scientists.
• Co-architect the scientific direction of the AI-for-Cell-Biology platform, partnering with AI/ML and Engineering leads.
• Own the translational BioML charter, converting foundational research into platform-deployable tools and capabilities.
• Anchor initial applied programs focused on target identification and evaluation for next-generation therapeutic discovery.
• Pioneer the use of autonomous-science capabilities by running closed-loop experiments and providing product-shaping feedback.
• Serve as a scientific liaison for product and partnership scoping and represent the team's research through external publications.

Requirements

• PhD in Computational Biology, Computational Genomics, Machine Learning, or a related quantitative field.
• Track record of impact in computational cell biology with publications in premier venues (Nature, Science, Cell, ICLR, ICML, or NeurIPS).
• Deep scientific fluency across modalities including single-cell omics, perturbation biology, spatial profiling, and imaging.
• Demonstrated experience in computational target identification or disease-mechanism mapping.
• Proven track record of hiring, growing, and leading computational scientists.
• Experience translating computational research into deployed capabilities that are consumed by downstream teams.

Nice to have

• Experience with Lab-in-the-Loop or closed-loop workflows where predictions drive experimental decisions.
• Background working with therapeutic-modality teams (cell therapy, nucleic-acid delivery, small molecule).
• Contributions to open-source tools, benchmarks, or datasets for applied computational cell biology.
• Experience in early-stage 0→1 environments.

Culture & Benefits

• Competitive base compensation with bonus potential and generous early-stage equity.
• Comprehensive U.S. and International benefit packages.
• High-velocity startup environment guided by values of truth, trust, curiosity, grit, and velocity.
• Opportunity to work at the frontier of AI and biology to tackle problems of historic importance.