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Description

We are looking for an exceptional senior applied scientist to join the AWS Applied AI Life Sciences organization. You will invent, implement, and deploy state of the art machine learning algorithms and intelligent AI systems to solve complex problems in healthcare and life sciences area, making a meaningful impact on patient lives. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists.

Key job responsibilities

- Design, develop, and deploy novel Agentic systems and ML solutions for complex healthcare challenges

- Navigate ambiguity and create clarity in early-stage product development

- Establish best practices for ML experimentation, evaluation, development and deployment

- Collaborate with product managers, engineers, and domain experts to transform research into production-quality features

- Mentor junior scientists and contribute to the technical strategy of the team

A day in the life

You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models.

About the team

We are a multidisciplinary team of product managers, engineers, scientists, and domain experts working at the intersection of AI/ML and healthcare. We leverage AWS's expertise in secure, scalable cloud computing and applied AI to solve complex challenges in healthcare and life sciences. Our team values customer obsession, technical excellence, innovation, and a commitment to improving patient outcomes through technology.

Diverse Experiences

AWS 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, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Basic Qualifications

- PhD, or Master's degree and 6+ years of applied research experience

- 5+ years of building machine learning models for business application experience

- Experience programming in Java, C++, Python or related language

- Experience with neural deep learning methods and machine learning

- Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, etc.)

- Applied Research experience in Biostatistics, Pharmacology, Pharmacometrics, or other related fields.

Preferred Qualifications

- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability

- Experience with predictive modeling in healthcare, pharmacology, or clinical trial contexts

- Experience working with healthcare data (e.g., EHR, clinical trials, medical claims)

- Familiarity with time series analysis, causal inference methods and explainable AI approaches

- Understanding of synthetic data generation techniques (e.g., GANs) for healthcare applications

- Experience in applying Generative AI and building Agentic systems.

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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.