Principal Scientist, Machine Learning
Flagship Pioneering, Inc.
| Company | Flagship Pioneering, Inc. |
| Category | Uncategorised |
| Location | Cambridge |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 5 Aug 2026 |
| Last verified | 6 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
ABOUT PIONEERING INTELLIGENCE Pioneering Intelligence builds on Flagship Pioneering’s legacy of founding cutting-edge science and computational ventures, harnessing recent advances in AI, machine learning, and data to accelerate fundamental research and create a portfolio of AI-first companies. As part of Flagship’s integrated model of science, entrepreneurship, and capital, it transforms breakthrough ideas into world-changing companies, elevating the AI advances happening across the ecosystem in human health, sustainability, and beyond.
THE ROLE We are seeking a Principal Scientist (Embedded ML/Computational) to lead AI/ML and computational projects that accelerate pharmaceutical R&D across the preclinical, translational, and clinical continuum, working closely with Pioneering Medicines (PM) and across Flagship’s platform companies as part of the company origination process. You will define and deliver pragmatic AI strategies and oversee method and platform development across omics, biomolecule design, multi-o, systems biology, and scientific literature mining, ensuring rigor in model development, benchmarking, scaling, and reporting. Throughout, you will use LLM-based agents and agentic workflows as the connective tissue that ties these methods into end-to-end pipelines scientists rely on. You will manage cross functional contributors as applicable, influence company direction, and represent PI to venture teams, PM, and external partners. The ideal candidate is a self-directed serial deep diver - someone who can move from protein design one week to multi-omics or docking pipelines the next, and wire them together with agents that automate scientific workflows.
KEY RESPONSIBILITIES
Program Leadership: Lead development, implementation, control, and reporting of several AI/ML and computational projects within assigned ventures and PM programs across the preclinical, translational, and clinical continuum, in line with broader strategic plans of PI and Flagship.
Technical Ownership: Own the build, scaling, benchmarking and maintenance of agentic systems that combine ML and computational biology tools (genomics,biomolecule design,literature mining,system biology, etc) which serve as end-toend systems for accelerating preclinical, translational and clinical R&D.
Best Practices: promote operational excellence in AI projects by educating cross-functional collaborators.
Team Leadership: Manage and/or coordinate internal and external scientists/engineers and crossfunctional project teams as applicable; mentor early hires; support recruiting and interview.
Planning & Resourcing: Contribute to project planning, including budgets, resources, and timelines; surface risks and tradeoffs early with clear options.
Landscape & Strategy: Independently scout emerging literature and the AI/ML and agentic-AI landscape; synthesize concepts to propose new development strategies and identify opportunities to accelerate R&D across the preclinical, translational, and clinical continuum for PI, PM, and venture portfolios.
Communication & Influence: Influence the course of projects and technical approaches; adapt and present complex findings to diverse audiences to support meaningful interpretation and action.
PROFESSIONAL EXPERIENCE & QUALIFICATIONS
Master’s, or PhD in a relevant field (e.g., machine learning, mathematics, statistics, computational sciences) with 5+ years' experience scientific/engineering/computational in academic, pharmaceutical, or biotechnology settings; industry AI/ML experience preferred.
Experience driving results directly or indirectly through teams of engineers/scientists in dynamic, fastpaced, entrepreneurial, and technical environments.
Clear evidence of sustained independent thought and creativity driving high impact, cross disciplina