# Principal Scientist, Machine Learning - Multimodal Biological Reasoning **Company**: Flagship Pioneering **Location**: Cambridge, MA **Experience**: senior **Job type**: full-time **Salary**: $216,000 - $297,000 **Category**: Data Science **Industry**: Healthcare **Apply**: https://job-boards.greenhouse.io/flagshippioneeringinc/jobs/8597814002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_540ac2ef-0b9 ## Description Pioneering Intelligence, a part of Flagship Pioneering, is seeking a Principal Scientist, Machine Learning - Multimodal Biological Reasoning. As a Lead, you will have the unique opportunity to shape our biological reasoning efforts on both the technical and application levels. You will be a hands-on lead for a team of talented machine learning scientists innovating on model architectures that will create best-in-class biological reasoning engines. Key Responsibilities: - Own the roadmap: lead the project from architecture and data exploration through model readiness, benchmarking, refinement, and agentic integration. - Guide technical architecture through a biological lens: guide multi-modal, multi-scale model design and ensure the system can ingest and reason over modalities relevant to mechanism-of-action reasoning, target discovery, perturbation biology, pathway reasoning, protein function, and autonomous discovery workflows. - Translate biology into model and evaluation requirements: ensure model development is driven by biological relevance that enables real scientific workflows, not just benchmark performance or technical elegance. - Build the engine for a novel science platform: develop and integrate reasoning engines into Pioneering Intelligence's AI Scientist platform for autonomous science. - Source and shape portfolio use cases: interface with Flagship teams and portfolio company end-users to identify use cases, source data assets, define success criteria, and create end-user feedback loops for reasoning engines that are scientifically meaningful, tractable, and answer high-value questions with real world application. - Communicate the impact: disseminate strategic direction and scientific results to Flagship stakeholders and in public forums. Qualifications: - 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 high-value use cases, identify data assets, define success criteria, and translate discovery 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. - Comfort operating in an entrepreneurial environment where the goal is not only to build a model, but to create a new capability that can reshape company creation and scientific discovery. Requirements: - 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. Benefits: - Healthcare coverage - Annual incentive program - Retirement benefits - Broad range of other benefits ## Skills ### Required - LLMs - multimodal modeling - representation learning - fine-tuning - post-training - benchmarking - ML systems - computational biology - AI-for-biology - AI-enabled drug discovery - translational data science - biological foundation models --- Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/flagshippioneeringinc/jobs/8597814002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)