Drimva

Amazon

Principal Applied Scientist - AI for Life Sciences, AWS Applied AI Solutions - Life Sciences

$199K–$269K

Seattle, WA · Principal · Full-time · Posted Sep 11, 2026

Experience
Experience as a senior or principal-level applied scientist; no number of years stated.
Education
PhD in Machine Learning, Computer Science, Computational Biology, or related field.

About the job

Sets research direction and develops life-sciences AI methods and products, translating frontier research into customer-ready capabilities for drug design and clinical workflows.

What you'll do

  • Lead research on LLM reasoning, agentic AI, and biological model customization; develop and validate methods for scientific and regulatory workflows.
  • Partner with customers and domain experts, and collaborate with product and engineering to deliver research as production-scale products.
  • Publish research, mentor applied scientists, and influence multi-year research roadmaps while contributing directly to research.

What they ask for

  • PhD in Machine Learning, Computer Science, Computational Biology, or a related field.
  • Senior- or principal-level applied scientist experience and a record of solving complex technical problems.
  • Expertise in LLMs, reasoning systems, agentic AI, and model customization; strong top-tier ML or computational biology publication record.
  • Life sciences or related scientific domain experience; experience translating research into products and launching 0-to-1 AI capabilities; strong Python and PyTorch or JAX skills.

Nice to have

  • Experience building managed AI services or model-as-a-service offerings for scientists.
  • Expertise in protein structure prediction, inverse folding, antibody optimization, clinical data standards, regulatory science, or model customization at scale; mentoring senior scientists.

Pay

198,900.00 - 269,000.00 USD annually (base salary)

Tools

LLMs, Python, PyTorch, JAX, RLHF, retrieval augmentation, domain adaptation, biological foundation models

AI focus

Develops and applies LLM reasoning, agentic AI, and biological foundation-model customization for drug discovery and clinical and regulatory workflows.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)