Applied Scientist, SAAR

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Job summary

Amazon Web Services is looking for world class scientists to join the Security Analytics and AI Research team within AWS Enterprise Security Services. This group is entrusted with researching and developing core 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 cyber security and experience with graph neural networks (GNN) or natural language processing (NLP), this will be an exciting opportunity.

The AWS Enterprise 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.

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 14 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 and enable them to take on more complex tasks in the future.

Key job responsibilities

• 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.

BASIC QUALIFICATIONS

• PhD in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field.
• 3+ years of working knowledge of graph neural networks (GNN) or natural language processing (NLP).
• 3+ years of hands-on experience in predictive modeling and analysis.
• 3+ years of algorithm development experience.
• 4+ years of coding with at least one of the following: Java, C++, Python, Scala, Rust or other programming language, as well as with R, MATLAB, or similar scripting language.

PREFERRED QUALIFICATIONS

• Track record of peer reviewed academic publications.
• 6+ years of relevant experience in GNN or NLP.
• Extensive experience in large scale machine learning system or distributed system.
• Strong verbal/written communication skills, including an ability to effectively collaborate with both research and technical teams.
• 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.
• 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.