Sr. Applied Scientist, AWS Applied AI Solutions Life Sciences
Seattle, WA - USA
Job Summary
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 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 clinical trials were building AI that automates and optimizes regulatory and clinical development drug design our products (including Amazon Bio Discovery) accelerate discovery by giving bench scientists AI-guided protein engineering and antibody design capabilities. 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 Applied Scientist to build the models and methods behind our life sciences AI products with a primary focus on clinical trial operations and agentic reasoning. You will design train and evaluate systems that reason over complex clinical and operational logic and ship them into products customers use directly. You will work closely with senior and principal scientists on well-scoped research problems own your results end to end and see your work reach production.
This role combines expertise in LLM reasoning and agentic AI with applied impact in life sciences. You will work on how large language models reason plan and act in complex scientific domains while applying domain knowledge 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 operational workflows
How do you evaluate agent reliability and faithfulness rigorously enough to trust in high-stakes clinical settings
How do you develop model customization methods (fine-tuning retrieval augmentation domain adaptation) that let customers get strong results from foundation models on their own data
You will focus on clinical trial operations (agentic automation structured reasoning evaluation domain adaptation) with opportunities to contribute across drug discovery (protein engineering antibody design) as the portfolio grows. You will own end-to-end scientific solutions from research through production and your work will directly shape the tools that scientists use daily.
Key job responsibilities
Design train fine-tune and evaluate LLM-based agentic systems that reason over clinical protocols regulatory standards and operational workflows
Build rigorous evaluation harnesses and benchmarks to measure agent reliability faithfulness and failure modes in high-stakes domains
Develop model customization methods (fine-tuning RLHF retrieval augmentation domain adaptation) that help customers get better outputs on their own data with less effort
Contribute to graph-based and causal modeling approaches for clinical trial operations
Partner with Life Sciences domain experts product and engineering to translate scientific challenges into shipped capabilities
Own experiments end to end: problem framing implementation evaluation iteration and hand-off to production
Publish at top-tier venues where the work supports it
Contribute to drug discovery efforts (protein engineering antibody design) as opportunities arise
A day in the life
Design and run an experiment to validate a new agentic reasoning or fine-tuning method then ship it as a capability customers can use
Diagnose why a model is failing on a new class of inputs and implement a fix to unblock a delivery milestone
Build or extend an evaluation benchmark to measure how faithfully an agent reasons over clinical logic
Meet with domain experts to scope what the next model release needs to do
Review results with a senior scientist sharpen the approach and get it over the finish line
Prototype a new idea that could become the next capability in the product
About the team
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home theres nothing we cant achieve in the cloud.
Here at AWS its in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences including our Conversations on Race and Ethnicity and AmazeCon conferences inspire us to never stop embracing our uniqueness.
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
- PhD or Masters degree and 6 years of applied research experience
- Experience programming in Java C Python or related language
- Experience with modeling tools such as R scikit-learn Spark MLLib MxNet Tensorflow numpy scipy etc.
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 - 167100.00 - 226100.00 USD annually
Required Experience:
Senior IC
About Company
Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa Devices, sporting goods, toys, automotive ... View more