The AWS 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.
Key job responsibilities
* Invent, implement, and deploy state of the art machine learning and deep learning models 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.
About the team
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Utility Computing (UC)
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of field experience in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field.
- Working knowledge of natural language processing (NLP) or large language model (LLM).
- Experience with unsupervised learning, semi-supervised learning and continual learning.
- Hands-on experience in predictive modeling and analysis.
- Algorithm development experience.
- Proficient in coding with at least one of the following: Java, C++, Python, Scala, Rust or other programming language.
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning.
PREFERRED QUALIFICATIONS
- 5+ years of relevant experience in NLP and LLM.
- 3+ years of relevant experience in unsupervised learning, semi-supervised learning and continual learning.
- Track record of peer reviewed academic publications.
- 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.
- Strong experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning.
- 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.
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.