Principal Scientist, Machine Learning - Multimodal Biological Reasoning

The role

You will lead a team of machine learning scientists to build multi-modal, multi-scale reasoning engines for biology. You will source use cases across Flagship and its portfolio companies to develop models for unconventional life sciences problems.

What you will do

• Own the project roadmap from architecture and data exploration through model readiness and agentic integration.
• Guide multi-modal, multi-scale model design for biological reasoning.
• Translate biology into model and evaluation requirements.
• Develop and integrate reasoning engines into the AI Scientist platform.
• Source and shape portfolio use cases by interfacing with Flagship teams and end-users.
• Communicate strategic direction and scientific results to stakeholders and public forums.

Required qualifications

• PhD, MS, or equivalent experience in computational biology, machine learning, bioengineering, computer science, systems biology, quantitative biology, translational science, or a related field.
• Experience in biotech, pharma, AI-for-science, AI drug discovery, venture creation, or a platform organization serving multiple scientific programs.
• Experience deploying AI/ML for biology systems into scientific workflows at enterprise scale.
• Experience with LLMs, biological foundation models, protein language models, genomic foundation models, scientific agents, or AI discovery platforms.
• Experience working across multiple internal and external customers, therapeutic programs, or discovery teams.
• Industry-leading expertise in modern LLMs, multimodal modeling, representation learning, fine-tuning, post-training, benchmarking, and ML systems.
• Deep experience in computational biology, AI-for-biology, AI-enabled drug discovery, translational data science, biological foundation models, or scientific discovery platforms.
• Demonstrated ability to work with scientists or biotech teams to scope use cases and translate needs into technical execution plans.
• Working knowledge of biological data modalities such as genomics, transcriptomics, perturbation data, protein sequence, protein structure, pathways, imaging, pathology, or time-series biological data.
• Strong judgment around mechanism-of-action reasoning, target discovery, perturbation biology, scientific credibility, model limitations, hallucination risk, interpretability, and validation.
• Experience leading small, high-caliber technical teams through ambiguous scientific or product problems.
• Ability to communicate clearly with ML researchers, data engineers, portfolio-company scientists, executives, and venture creation leaders.

Benefits

• Healthcare coverage
• Annual incentive program
• Retirement benefits
• Broad range of other benefits

About the company

Pioneering Intelligence builds on Flagship Pioneering’s legacy of founding cutting-edge science and computational ventures. It transforms breakthrough ideas into world-changing companies by harnessing AI, machine learning, and data.