Teams at Flagship Pioneering

Design, build, and own scalable data infrastructure for proteomics research and machine learning. Responsibilities include developing production data platforms and pipelines, integrating instruments and LIMS, creating cloud infrastructure with infrastructure-as-code and CI/CD, ensuring data integrity and lineage, and transforming raw experimental data into reliable ML-ready datasets. The role partners closely with scientific teams, establishes engineering standards, sets technical direction, and mentors colleagues.

Lead product strategy and execution for Iris Chat, an AI-powered psychological fitness product. Own product vision, customer journeys, activation, retention, conversion, subscription value, experimentation, and AI quality. Manage product, design, engineering, and AI research teams; hire and develop leaders; balance research and delivery; and establish standards for evaluation, privacy, safety, reliability, and user trust. Partner with leadership to build a focused roadmap and durable consumer business.

Develop evolutionary algorithms for autonomous scientific discovery, enabling populations of models, hypotheses, programs, and representations to evolve through iterative search, selection, evaluation, and recombination. Build Bayesian and probabilistic methods for candidate ranking, uncertainty estimation, diversity preservation, and quality measurement. Establish benchmarks, integrate algorithms into autonomous-science pipelines, publish research, guide technical direction, and mentor colleagues as a senior individual contributor.