Senior Scientist, Multimodal Biological Reasoning

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.

Pioneering Intelligence is seeking a Senior Scientist for Flagship's ambitious efforts to build polyintelligent AI systems that unify human scientific expertise, machine intelligence, and nature’s biological signals into multi-modal, multi-scale reasoning engines for biology.

As a Senior Scientist, you will have the unique opportunity to shape our biological reasoning efforts on both the technical and application levels. You will be a key contributor on a team innovating on machine learning model architectures that will create best-in-class biological reasoning engines that tackle the unconventional life sciences problems that Flagship pursues. You will work with teams in Pioneering Intelligence and Flagship-at-large to apply our reasoning engines to discover new biology and engineer new biological solutions through massively parallel in-silico reasoning.

• Design technical architecture, training strategies, and evaluations for a multi-modal, multi-scale biological reasoning model.
• Train and validate large-scale biological reasoning models.
• Development and curation of novel biological datasets. Construct new datasets and benchmarks to empirically evaluate biological validity and generalization.
• Translate biological questions into well-defined ML problems, build and scale training data pipelines and model benchmarks for downstream applications.
• Contribute to the technical and product roadmap, data strategy and research priorities.

• PhD in Computer Science, Machine Learning, Computational Biology, Systems Biology or related quantitative field (or Master’s with equivalent research experience).
• Strong machine learning and software engineering fundamentals.
• Experience handling and processing large scale biological datasets.
• Ability to work independently in an ambiguous environment, foster cross-team collaborations, and communicate externally.
• Demonstrated ability to work in cross-functional settings with scientists or biotech teams to bridge needs and technical implementation.

• Experience pre-training, fine-tuning and/or post-training large foundation models (e.g. billion+ parameter LLMs or VLMs) or foundation models in biology (e.g. ESM, Evo2, Carbon, Nucleotide Transformer, UCE, CellFM, Transcript Former, etc.)
• Experience with multi-modal machine learning, particularly non-text modalities.
• High impact contributions in relevant venues, such as major product releases within a company, publications (NeurIPS, ICML, ICLR, Nature, Science, Cell, etc.), or open-source contributions in AI for Science.
• Experience with causal reasoning, especially as relevant to perturbation biology, pathways, and/or mechanism-of-action reasoning
• Fluency in at least one life science domain (molecular biology, genetics, biochemistry, cell biology, structural biology, biophysics, bioengineering, or related)
• Experience deploying AI/ML into scientific workflows at enterprise scale.
• Familiarity with distributed training infrastructure