Principal ML Scientist: Embedded AI for Drug Discovery

Flagship Pioneering; Cambridge (MA); On-site; USD 208,000 - 286,000; Full time

Benefits offered by this job

Healthcare coverage

Annual incentive program

Retirement benefits

Job summary

Flagship Pioneering’s Pioneering Intelligence seeks a Principal Scientist (Embedded ML/Computational) to lead AI/ML and computational projects accelerating pharmaceutical R&D from preclinical to clinical stages.

You will define pragmatic AI strategies, oversee method and platform development across omics, biomolecule design, and literature mining, and coordinate cross-functional teams to deliver end-to-end pipelines using agentic workflows.

Qualifications

• Master’s or PhD in a relevant field with 5+ years' experience in scientific/engineering/computational settings; industry AI/ML preferred.
• Experience leading teams of engineers/scientists in dynamic environments; demonstrated impact.
• Proven track record of independent thought and high-impact AI/ML projects.
• Leadership and decision-making contributions on AI/ML model progression.

Responsibilities

• Lead development, implementation, and reporting of AI/ML and computational projects across PM programs.
• Own build, scaling, benchmarking of agentic systems for end-to-end preclinical to clinical R&D.
• Promote operational excellence and educate cross-functional collaborators.
• Manage internal and external scientists/engineers and cross-functional teams; support recruiting.
• Contribute to project planning including budgets, resources, and timelines.

Skills

Python

PyTorch/JAX

AI/ML leadership

Version control

Databases

Education

Master’s or PhD in a relevant field

Tools

Pydantic AI

LangGraph

LangChain

CrewAI

AutoGen

Job description

Flagship Pioneering’s Pioneering Intelligence seeks a Principal Scientist (Embedded ML/Computational) to lead AI/ML and computational projects accelerating pharmaceutical R&D from preclinical to clinical stages.

You will define pragmatic AI strategies, oversee method and platform development across omics, biomolecule design, and literature mining, and coordinate cross-functional teams to deliver end-to-end pipelines using agentic workflows.