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Applied Scientist, AWS Security, AWS Security

Job ID: 2249305 | Amazon Web Services, Inc.


Job summary
Join us in building innovative services that protect AWS from security threats!

As an Amazon Security Applied Scientist, you’ll help build and manage services that detect and automate the mitigation of cybersecurity threats across Amazon’s infrastructure. You’ll work with security engineers, software development engineers, and other scientists across multiple teams to develop innovative security solutions at massive scale. Our services protect the AWS cloud for all customers and preserve our customers’ trust in us. You’ll get to use the full power and breadth of AWS technologies to build services that proactively protect every single AWS customer, both internally and externally, from security threats – not many teams can say that!

Our team is dedicated to supporting new team members. The team has a mix of experience levels, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior engineers, scientists, and managers truly enjoy mentoring junior engineers, junior scientists, and engineers from non-traditional backgrounds through one-on-one mentoring and code reviews.

We care about your career growth. We assign projects and tasks based on what will help team members develop into more well-rounded scientists and enable them to take on more complex tasks in the future.

Our team is intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. Yes, we do get to build a cool service, but we also believe a big reason for that is the inclusive and welcoming culture we cultivate every day.

We’re looking for a new teammate who is enthusiastic, empathetic, curious, motivated, reliable, and able to work effectively with a diverse team of peers. We want someone who will help us amplify the positive & inclusive team culture we’ve been building.

About Us

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 (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.

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.

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 Electrical Engineering, Computer Science, Mathematics or Physics with specialization in natural language processing, machine translation, signal processing, or machine learning.
  • Breadth and depth knowledge of ML learning algorithms.
  • Experience leveraging ML within security.
  • 5+ years of relevant experience in industry and/or academia.
  • Familiarity with programming languages such as Python, Java, C/C++ or Perl.


  • Proven track record of successfully applying ML-based solutions to complex problems in business, science, or engineering.
  • Experience in building natural language processing, natural language understanding and dialogue systems (e.g., commercial products or government projects)
  • Solid Machine Learning background and hands-on experience with neural deep learning methods.
  • Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.
  • Solid software development experience.
  • Good written and spoken communication skills.

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