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Amazon Principal Applied Scientist, AWS Health AI in Seattle, Washington

Description

Are you passionate about leveraging AI to revolutionize healthcare and life sciences? AWS Health AI is seeking a visionary Principal Applied Scientist to lead the research and development of applications that reimagine the experiences life sciences researchers and healthcare practitioners. As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.

As Principal Applied Scientist, you'll lead pioneering research in AI-driven protein design and antibody engineering. You’ll guide a team of scientists to invent and simplify on behalf of life sciences researchers and define novel, generative AI agent based experiences to help those researchers accelerate drug discovery. You will also drive innovation by integrating computational design pipelines with laboratory workflows, creating efficient systems for rational therapeutic design. This is a highly visible and impactful role within AWS, offering the opportunity to shape the future of healthcare technology and drive innovation at a global scale. You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will be technically fearless, with a passion for building scalable science and engineering solutions.

Key job responsibilities

What You'll Do:

  • Lead a team of talented applied scientists in solving complex healthcare challenges

  • Develop novel algorithms and modeling techniques for multimodal systems

  • Drive the science roadmap and innovation strategy for AWS Health AI

  • Collaborate with cross-functional teams to create impactful products and services

  • Conduct cutting-edge research and publish in top-tier conferences and journals

About the team

  • Work on meaningful problems that improve lives globally

  • Access to cutting-edge technology and vast resources

  • Collaborate with world-class researchers and engineers

  • Opportunity to publish and present at top conferences

  • Shape the future of AI in healthcare

Basic Qualifications

BASIC QUALIFICATIONS

What We're Looking For:

  • Strong background in deep learning and multimodal systems

  • Passion for applying AI to healthcare challenges

  • Ability to lead and mentor research teams

  • Experience in developing scalable, secure AI/ML systems

  • Expertise in areas such as medical imaging, genomics, or clinical decision support

  • Excellent communication and collaboration skills

  • PhD with specialization in artificial intelligence, natural language processing, machine learning, biomedical engineering, bioinformatics, medical imaging, genomics, or computational cognitive science

  • 8+ years of combined academic and research experience using ML to solve problems in natural language processing (NLP), computer vision (CV), computer speech (ASR), and/or other AI domains. Health-domain preferred.

  • Be a thought-leader: bring passion for innovation and a drive to solve challenging problems that can have a significant impact on healthcare and human well-being

  • Can successfully sell ideas to an executive level decision maker.

  • Mentors and trains the research scientist community on complex technical issues.

  • Excellent communication and collaboration skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical audiences.

  • Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch)

  • Experience with cloud computing platforms, preferably AWS

Preferred Qualifications

  • Proven track record of leading and delivering successful AI/ML projects in healthcare or life sciences domains, with a deep understanding of the challenges and opportunities in these fields.

  • Strong programming skills and experience with machine learning frameworks and tools, such as TensorFlow, PyTorch, scikit-learn, and AWS AI/ML services.

  • Experience with deep learning frameworks, LLMs and multimodal architectures

  • Experience with healthcare data types (e.g., EHRs, medical imaging, genomics) and familiarity with healthcare regulations (e.g., HIPAA, GDPR)

  • Strong publication record in top-tier journals and conferences

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/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.

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