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Principal Applied Scientist, AWS AI Research and Education

Job ID: 1834087 | Amazon Dev Center U.S., Inc.


Job summary
AWS AI/ML is looking for world class scientists to join its AI Research and Education group, which brings science and science-related engineering work to Amazon’s cloud-based AI services, open source libraries, and education projects. In this role, you will work with your peers and senior management to set direction for Amazon’s AI efforts. Our mission is to put the power of AI in the hands of every developer. You will lead our efforts in AutoML, including both the research side and the open source library, AutoGluon. You will be responsible for mentoring a team of applied scientists and develop top talent. You will partner with engineering leaders to deliver remarkable new AWS services and features that leverage Machine Learning, Deep Learning, and AutoML.

As a Principal Applied Scientist, you will identify science problems, create roadmaps for forward-looking research, communicate them to senior leadership, and work closely with engineering teams to bring research to production. You will work with teams of talented scientists and fill the ranks by attracting the best scientists in machine learning. You will work with talented peers and leverage Amazon’s heterogeneous data sources and large-scale computing resources.

Key job responsibilities
· Map business requirements and customer needs to a scientific problem.
· Align the research direction to business requirements and make the right call on research/development schedule and prioritization.
· Research, design and supervise the implementation of scalable machine learning (ML) models for AutoML, and/or other scalable computational models to solve problems that matter to our customers in an iterative fashion.
· Mentor and develop junior applied scientists and developers who work on data science problems in the same organization.
· Stay informed on the latest machine learning, deep learning, and/or artificial intelligence trends and make presentations to the larger engineering and applied science communities.

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 16 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 projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.


· PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related quantitative field and strong knowledge of machine learning.
· 10+ years of professional experience in applied science and/or based research fields.
· 10+ years leading the development of systems using advanced Machine Learning concepts.
· Demonstrated leadership experience.
· Excellent communication skills.


· Strong research track record and publications at top-tier peer-reviewed conferences or journals.
· Depth and breadth in state-of-the-art automatic machine learning technologies.
· Experience designing, developing and launching customer-facing products and services using machine learning.

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