Applied Scientist

Job ID: 1363053 | Amazon Web Services, Inc.

DESCRIPTION

The Machine Learning Product Teams are responsible for identifying customer needs and building products and services to meet those needs. As a member of the AWS team, you will work side-by-side with the Product Teams to continue to build the products and services designed with fairness and explainability in mind.

As a Scientist on this team, you will:
· help define the strategies, priorities and metrics of the team for fairness and explainability and and execute for delivery,
· help build and develop the AWS team, as needed,
· understand in depth the technical and scientific issues related to machine learning fairness, and
· serve as liaison to internal and external stakeholders.

BASIC QUALIFICATIONS

· Advanced degree (e.g., M.S. or PhD) in computer science, statistics, engineering, mathematics or relevant discipline, ideally with a research or engineering focus on algorithmic fairness and explainability in machine learning and related topics
· 2+ years of experience in either machine learning, data science, or related disciplines.
· Experience with machine learning applications
· Experience working with software engineering teams


PREFERRED QUALIFICATIONS

· Passion for reducing bias in machine learning systems.
· Willingness to engage with academic community working on fairness and explainability.
· Ability to work well with Product Team colleagues without control via direct reporting line.
· Ability to synthesize large amounts of complex data and to communicate high-level concepts effectively to internal and external stakeholders.

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, visit https://www.amazon.jobs/en/disability/us