From Amazon's posting. “We” and “our” refer to the employer.
AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are.
We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset.
The Healthcare AI organization in AWS is seeking an Applied Science Manager to lead science and data teams working on innovative AI-powered healthcare solutions. We are developing innovative products that leverage generative and agentic AI to transform clinical and administrative workflows for healthcare providers. Our aim is to improve patient care, enhance operational efficiency, and deliver exceptional value to our customers.
You will lead a team of applied scientists working on transformative healthcare solutions powered by cloud computing and artificial intelligence. This role offers an opportunity to work at the forefront of applied AI/ML and distributed systems building new products and services from the ground up.
Our team builds on our existing successful healthcare business which serves major providers and payers in the US. You'll be instrumental in creating solutions that address complex challenges in areas such as clinical documentation, health data analytics, and accurate billing, ultimately contributing to better health outcomes for individuals and populations.
Key job responsibilities
As an Applied Science Manager you will be responsible for building and leading a world-class team that pushes the boundaries of computer vision machine learning and artificial intelligence.
In this role you will drive the technical vision and strategy for your team while fostering a culture of innovation and scientific excellence. You will balance hands-on technical leadership with people management responsibilities ensuring your team delivers innovative solutions while growing professionally. The role requires someone who can think strategically about business problems while diving deep into technical details when needed.
Building and mentoring teams of Applied Scientists and ML Engineers
Setting technical direction and research strategy aligned with business goals
Driving innovation in medical administration reasoning systems, AI agent design, and medical coding
Collaborating with cross-functional teams to translate research into production
Managing project portfolios and resource allocation
A day in the life
Inclusive Team Culture
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign opportunities based on what will help each team member develop into a better-rounded contributor.
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, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
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.
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, there's nothing we can't achieve in the cloud.
Here at AWS, it's 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.
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.
Basic Qualifications
2+ years of scientists or machine learning engineers management experience
Knowledge of ML, NLP, Information Retrieval and Analytics
PhD, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience
Experience in applied research
Experience programming in Java, C++, Python or related language
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred Qualifications
Experience building machine learning models or developing algorithms for business application
Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
Experience building speech recognition and natural language processing systems (like commercial speech products or government speech projects) as academic or professional work
Equal Opportunity
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.
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 https://amazon.jobs/en/benefits.
USA, WA, Seattle - 183,800.00 - 248,700.00 USD annually
About this listing
LAYIQ is an independent job-discovery service. This listing does not imply a partnership with or endorsement by the employer. Review the original posting for current details and availability.
