Amazon Applied Scientist Security Analytics AI Research SAAR 

United States, Washington, Seattle 

943693029

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.Utility Computing (UC)Work/Life Balance
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.

- 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.

- 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.