The Amazon SageMaker Low-Code/No-Code team is looking for a passionate, highly skilled, and inventive Senior Applied Scientist with a strong machine learning background to lead the development and implementation of state-of-the-art automated ML systems that aid the jobs of a data scientist and machine learning engineer with automation.


As an Applied Scientist, you will play a critical role in driving the understanding of the development of automation techniques for machine learning and data science. You will handle Amazon-scale use cases with significant impact on our customers' experiences. Our team thrives on white-box understanding of machine learning and a connection to scientific principles (in addition to mathematical and statistical principles).


Key Job Responsibilities

  1. Create objective functions for automation of machine learning and data science.
  2. Innovate new methods for evaluation, simplification, and creation of models for classification, regression, forecast, and language modeling.
  3. Research in advanced customer understanding and behavior modeling techniques.
  4. Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in personal knowledge aggregation, processing, modeling, and verification.
  5. Design and execute experiments to evaluate the performance of state-of-the-art algorithms and models, and iterate quickly to improve results.
  6. Think Big about the arc of development of conversational assistant system personalization over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems.
  7. Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports.
  8. Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team.

A Day in the Life

  1. Create prototypes.
  2. Educate engineers on design and implementation issues of automated machine learning systems.
  3. Help engineers with customer requests.

About the Team

The LCNC team uses statistical, information-theoretic, and physical methods to automate the creation, tuning, and evaluation of models and to create data insights. We work across multiple AWS products, including AWS Sagemaker, to enhance the user experience by bringing more personal context and relevance to customer interactions.


Minimum Requirements

  1. PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
  2. Experience in patents or publications at top-tier peer-reviewed conferences or journals.
  3. Experience programming in Java, C++, Python or related language.
  4. Experience in professional software development.
  5. 3+ years of building machine learning models or developing algorithms for business application experience.
  6. Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.

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 for more information.


This position will remain posted until filled. Applicants should apply via our internal or external career site.

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