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