Applied Scientist I, Health AI

Amazon Web Services
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Job Description

Job summary
The Health AI team is looking for an Applied Scientist to join Health AI. Our products include Amazon Comprehend Medical and Amazon HealthLake. You will be involved in the entire product development cycle including customer calls, planning, design, prototyping, launching, and managing operations. Our products that make it easy for Healthcare customers to use Machine Learning to get better outcomes. You will work with a diverse team brought together and motivated by work that improves people’s lives, while being challenged on a daily basis.

Our ideal candidates thrive in ambiguity, build collaborative relationships, moves fast, and are passionate about meaningful work. They will have the technical skills to design and build complex distributed systems that runs at AWS scale. They prefer working on small, focused teams, own their product, and love to pitch in anywhere to get the job done. They lead by example and the team naturally gravitate towards them because of their engineering expertise and decision-making ability. They can communicate effectively with a wide variety of audiences and are comfortable pitching new ideas.

Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Amazon Science ( ( gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields.

Key job responsibilities

  • Applying latest deep learning and natural language processing techniques to ship new features for our customer
  • Convert ambiguous business questions into precise science problems
  • Regularly ship deep learning models and natural language processing models that run at AWS scale
  • Collaborate with engineers and product managers to deliver your solutions

About the team
Inclusive Team Culture
Here at AWS, 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 (gender diversity) 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. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.


  • Masters degree in a quantitative field (computer science, electrical engineering, mathematics, physics, or similar)
  • 3+ years of hands-on experience (academic or industrial) building ML models
  • At least one publication, as first author, in a leading conference or journal related to machine learning, natural language processing, or information retrieval
  • Sound theoretical understanding of broad machine learning concepts, with deep and demonstrable expertise in at least one topic or application of machine learning
  • Strong coding and problem-solving skills in at least one programming language such as Python, Java, C++, etc.
  • Fluency in written and spoken English


No candidate is perfect, and we do not expect you to meet all, or even most, of the qualifications below. If you have one or more of these qualifications, we will be very excited to receive your application!

  • PhD in Computer Science, Mathematics, or equivalent technical field.
  • Experience in building NLU, NLG, and/or ER systems, e.g., commercial NLU products or government NLU projects
  • Experience on working with conversations and knowledge Graphs

Company Info.

Amazon Web Services

Amazon Web Services, Inc. (AWS) is a subsidiary of Amazon providing on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis. These cloud computing web services provide a variety of basic abstract technical infrastructure and distributed computing building blocks and tools. One of these services is Amazon Elastic Compute Cloud (EC2).

  • Industry
    Information Technology
  • No. of Employees
  • Location
    410 Terry Ave N, Seattle, WA, USA
  • Website
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