Amazon Web Services is looking for world class scientists to join the Security Analytics and AI Research team within AWS Security Services. This group is entrusted with researching and developing core data mining and machine learning algorithms for various AWS security services like GuardDuty (https://aws.amazon.com/guardduty/) and Macie (https://aws.amazon.com/macie/). In this group, you will invent and implement innovative solutions for never-before-solved problems. If you have passion for security and experience with large scale machine learning problems, this will be an exciting opportunity.
The AWS External Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services.
Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work.
· Invent, implement, and deploy state of the art machine learning algorithms and systems for information security applications.
· Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.
· Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services.
· Report results in a scientifically rigorous way.
· Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for.
· Work closely with a mentor to expand your career with AWS
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 we 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.
Our team puts a high value on work-live 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. 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.
· PhD in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
· 2+ years of hands-on experience in predictive modeling and analysis
· 2+ years of algorithm development experience
· 2+ years of coding with at least one of the following: Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language
· 1+ years of working knowledge of Apache Spark and Scala
· 1+ years of experience with information security, threat detection or related domain
· Track record of peer reviewed academic publications.
· Strong verbal/written communication skills, including an ability to effectively collaborate with both research and technical teams.
· 10+ years of relevant experience in industry and/or academia.
· Extensive experience applying theoretical models in an applied environment.
· Expertise on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian Non-Parametric methods.
· Strong Experience in Structured Prediction and Dimensionality Reduction.
· Experience with defining organizational research and development practices in an industry setting
· Domain experience with threat detection techniques
· Track record of developing novel algorithms to help detect stealthy zero-day attacks
· Meets/exceeds Amazon’s leadership principles requirements for this role
· Meets/exceeds Amazon’s functional/technical depth and complexity for this role
· Able to work in a diverse team
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