Sr. Applied Scientist- P13n

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

Amazon is seeking an Applied Scientist to build next-generation ML systems for personalization in their e-commerce platform. The role involves applying state-of-the-art science and research, including Generative AI, LLMs, transformers, sequence models, and reinforcement learning, into production to enhance customer shopping experiences. The scientist will work on large-scale machine learning systems, leverage petabytes of data, and contribute to the science roadmap of personalization.

What you'd actually do

  1. As an Applied Scientist on the team you will be working on the state of art ways to help customers find the right products and content on their shopping journey.
  2. We are investing in multiple fronts including but not limited to GenerativeAI, LLMs, transformers, sequence models, reinforcement learning.
  3. This is an opportunity to come in on Day0 and influence the science roadmap of one of the most interesting problem spaces at Amazon - understanding the Amazon customer to build deeply personalized and adaptive shopping experiences.
  4. We will be working on applying state of the art science and research into production to elevate the customer experience.
  5. You will be part of a multidisciplinary team, working on one of the largest scale machine learning systems in the company.

Skills

Required

  • building machine learning models for business application
  • applied research
  • deep learning
  • reinforcement learning
  • Java
  • C++
  • Python

Nice to have

  • modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy
  • large scale distributed systems such as Hadoop, Spark

What the JD emphasized

  • building machine learning models for business application experience
  • applied research experience
  • neural deep learning methods and machine learning

Other signals

  • building next-generation ML systems
  • applying state of the art science and research into production
  • building scalable industrial systems
  • delivering state of the art customer experiences