Senior Applied Scientist, Personalization and Privacy AI Science, AWS AI/ML

1 day ago


Santa Clara CA United States Amazon Full time
Senior Applied Scientist, Personalization and Privacy AI Science, AWS AI/ML

Job ID: 2774822 | Amazon Development Center U.S., Inc.

As a Senior Scientist at AWS AI/ML leading the Personalization and Privacy AI teams, you will have deep subject matter expertise in the areas of recommender systems, personalization, generative AI and privacy. You will provide thought leadership on and lead strategic efforts in the personalization of models to be used by customer applications across a wide range of customer use cases. Particular new directions regarding personalizing the output of LLM and their applications will be at the forefront. You will work with product, science and engineering teams to deliver short- and long-term personalization solutions that scale to large number of builders developing Generative AI applications on AWS. You will lead and work with multiple teams of scientists and engineers to translate business and functional requirements into concrete deliverables.


Key job responsibilities

You will be a hands on contributor to science at Amazon. You will help raise the scientific bar by mentoring, educating, and publishing in your field. You will help build the scientific roadmap for personalization, privacy and customization for generative AI. You will be a technical leader in your domain. You will be a strong mentor and lead for your team.


About the team

The DS3 org encompasses scientists who work closely with different AWS AI/ML product services, innovating on the behalf of our customers customers.


BASIC QUALIFICATIONS
  1. 3+ years of building machine learning models for business application experience
  2. PhD, or Master's degree and 6+ years of applied research experience
  3. Experience programming in Java, C++, Python or related language
  4. Experience with neural deep learning methods and machine learning

PREFERRED QUALIFICATIONS
  1. Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  2. Experience with large scale distributed systems such as Hadoop, Spark etc.

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.

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