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Amazon Senior Applied Scientist Amazon CloudWatch Logs 
United States, Washington, Seattle 
551729380

20.11.2024
DESCRIPTION

Key job responsibilities
As a Sr. Applied Scientist you will be responsible for* Research and development of algorithms that improve training of foundation models across pre-training, multitask learning, supervised finetuning, and reinforcement learning from human feedback
* Research and development of novel approaches for anomaly detection, root cause analysis, and provide intelligent insights from vast amounts of monitoring and observability data* Lead key science initiatives in strategic investment areas of AI/ML/LLM Ops and Observability
* Be an industry thought leader representing Amazon at top-tier scientific conferences
* Engaging in the hiring process and developing, growing, and mentoring junior scientistsA day in the lifeWhy AWS
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.

BASIC QUALIFICATIONS

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Ability to translate informal customer requirements into problem definitions, dealing with ambiguity and competing objectives.


PREFERRED QUALIFICATIONS

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Excellent written and verbal communication skills, with the ability to present complex technical information in a clear and concise manner to a variety of audiences.