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

As part of the AWS Applied AI Solutions organization we have a vision to provide end user applications leveraging Amazons unique experience and expertise that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazons real-world experience to build opinionated turnkey solutions. Where customers prefer to buy over build we become their trusted partner with solutions that are easy to adopt and easy to use.

The Team

Join the next science revolution at AWS Life Sciences Applied AI Solutions where youll work alongside world-class scientists to build AI that transforms how therapeutics are discovered developed and brought to patients.

Were out to revolutionize how medicines are discovered developed and brought to patients powered by a new generation of AI. Our team tackles some of the hardest open problems at the intersection of frontier AI and life sciences. We apply biological foundation models large language models and agentic reasoning systems to life sciences problems then put them into the hands of pharma biotech and diagnostics customers as applications and managed services they can fine-tune tailor and deploy on their own data. The science challenges are deep: how do you design agentic systems that reason correctly over complex biological regulatory and clinical logic How do you enable customers to tailor foundation models to their proprietary data and get better outputs with less effort How do you adapt models to reason faithfully in high-stakes scientific and regulatory domains

Today were focused on two drug design our products (including Amazon Bio Discovery) accelerate discovery by giving bench scientists AI-guided protein engineering and antibody design clinical trials were building AI that automates and optimizes regulatory and clinical development workflows. We combine frontier research with production-scale delivery to put breakthrough science into the hands of customers solving humanitys hardest problems.

We value scientific rigor encourage publication and support conference participation. If you want to do research that ships this is the team.

The Role

We are seeking an exceptional Principal Applied Scientist to set the scientific direction for our life sciences AI portfolio. You will be the scientific leader who defines research agendas architects novel approaches and delivers models and methods that give our customers capabilities that did not previously exist.

This is a rare role that combines deep expertise in LLM reasoning and agentic AI with applied impact in life sciences. You will innovate on how large language models reason plan and act in complex scientific domains while applying domain knowledge in biology to ensure models produce scientifically valid outputs. The problems span multiple fronts:
- How do you build LLM-based agentic systems that correctly reason over clinical protocols regulatory standards and complex multi-step scientific workflows
- How do you develop model customization and training methods that let customers get state-of-the-art results from foundation models
- How do you adapt and extend protein and antibody models so customers can fine-tune on proprietary sequence data and get therapeutically relevant outputs

You will work across drug discovery (protein engineering antibody design) and clinical trial operations (agentic automation structured reasoning domain adaptation). You will own end-to-end scientific solutions from research through production and your work will directly shape the tools that thousands of scientists use daily.

Key job responsibilities
- Set the scientific vision and research agenda for LLM reasoning agentic AI and biological model customization across the portfolio
- Innovate on LLM reasoning planning and agentic approaches for complex scientific and regulatory workflows
- Develop model customization methods (fine-tuning RLHF retrieval augmentation domain adaptation) that enable customers to train better models on their own data with less effort
- Advance methods to adapt and extend biological foundation models for customer-specific therapeutic applications
- Solve open research problems in faithful reasoning multi-step planning and tool use in high-stakes scientific domains
- Partner with Life Sciences domain experts and customers to understand their hardest scientific challenges and translate those into tractable research problems
- Publish at top-tier venues and build the teams external scientific reputation
- Mentor applied scientists across the team while maintaining significant personal research contribution
- Collaborate with product and engineering to ensure research translates into shipped products that serve customers at scale
- Influence multi-year research roadmaps through deep scientific expertise and customer understanding


A day in the life
- Push a new reasoning approach into production that measurably improves outputs for a pharma customers workflow
- Design and run experiments to validate a novel fine-tuning method then ship it as a capability customers can use immediately
- Unblock a delivery milestone by diagnosing why a model is failing on a new class of inputs and implementing a fix
- Meet with a customers scientific team to scope what the next model release needs to do for them
- Review a teammates experimental results sharpen the approach and help get it over the finish line
- Publish results from shipped work at a top venue closing the loop between research and impact
- Prototype a new idea that could become the next major capability in the product

- PhD in Machine Learning Computer Science Computational Biology or related field
- Experience as a senior or principal-level applied scientist with a track record of solving complex technical problems
- Deep expertise in LLMs reasoning systems and agentic AI including architecture design training fine-tuning and optimization
- Strong publication record at top-tier ML or computational biology venues
- Demonstrated ability to innovate on model customization techniques (fine-tuning RLHF retrieval augmentation domain adaptation) and make models work for specific downstream applications
- Domain experience in life sciences computational biology or related scientific fields (protein engineering antibody design clinical data or regulatory science)
- Experience translating research into products or services that others use (not just standalone publications)
- Experience building and launching 0-to-1 AI products or capabilities from initial research through first customer delivery
- Excellent programming skills in Python and deep learning frameworks (PyTorch JAX) with a modern development practice that embraces AI-assisted coding and iteration

- Experience building managed AI services or model-as-a-service offerings that scientists use directly
- Deep expertise in protein structure prediction inverse folding or antibody optimization using AI
- Demonstrated experience with clinical data standards or regulatory science
- Experience with model customization at scale: efficient fine-tuning RLHF retrieval-augmented generation or domain adaptation
- A history of mentoring senior scientists and helping them achieve career breakthroughs

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Seattle - 198900.00 - 269000.00 USD annually