Applied Science Manager, Healthcare AI
at Amazon
Location
Seattle, Washington, USA
Compensation
$184k–$249k USD
Type
full time
Posted
4 months ago
Market range · company + function + seniority
p25 · target · p75 · n=128
Posted $249k · in the market band
Posting health
Aging · 65- ·Open 130 days
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Job description
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
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. - 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 - 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
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
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