Senior Computational Biologist (AI/ML)

TL;DR

Senior Computational Biologist (AI/ML): Accelerating scientific insight from population-scale immune organoid data by developing and stress-testing analytical approaches with an accent on designing robust modeling for complex, noisy biological measurements. Focus on integrating multi-omics data, characterizing immune responses, and identifying what changes under perturbation using AI and machine learning methods.

Location: On-site, San Francisco, CA, USA

Company

hirify.global is a fast-paced, venture-backed company leveraging human immune organoids with AI and machine learning to discover safer, more effective immunotherapies.

What you will do

• Invent and adapt modeling approaches for immune organoid data, including donor-aware inference, hierarchical models, and robustness to batch effects.
• Own analysis for immune phenotyping across various high-dimensional biological data types, integrating transcriptomic, proteomic, and functional data.
• Guide experiments with quantitative thinking, propose designs, and establish statistical best practices for analysis.
• Own the integrity of analytical datasets, develop data quality standards, and partner with engineers to transition pipelines to production.
• Generate clear, publication-quality visualizations and communicate findings to diverse audiences.

Requirements

• Strong quantitative foundation (statistics, applied math, CS, engineering, or equivalent) and a track record of solving ambiguous modeling and data analysis problems.
• Experience analyzing high-dimensional biological data (single-cell, cytometry, proteomics, functional assays, or similar).
• Immunology knowledge through formal training or hands-on research.
• Proficiency in Python and/or R for rapid, readable prototyping, with version control as standard practice.
• Ability to translate across disciplines and drive work to completion in a fast-moving environment.

Nice to have

• Experience with Bayesian/hierarchical modeling, causal inference, mechanistic-statistical hybrids, or ML approaches for biological data.
• Experience with organoid systems or primary human tissue models.
• Experience partnering with engineers to productionize data products.
• Track record training and stress-testing models on large biological datasets, with attention to generalization, robustness to distribution shift, and reusable representations.
• Familiarity with cloud/cluster computing for scaling analyses.

Culture & Benefits

• Work for a fast-paced, venture-backed company at a pivotal moment of growth.
• Join a team creating new tools to push the boundaries of medicine.
• Opportunity to leverage the human immune system to unlock safer, more effective drugs.
• Commitment to fostering an inclusive and respectful workplace.
• Equal opportunity employer.