Sr. Applied Scientist, Selling Partner Communities (spc)

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

Sr. Applied Scientist role focused on developing and implementing AI/ML solutions to improve the Amazon Selling Partner experience. This involves building scalable models, analyzing data, and staying current with LLM, RL, and agent-based AI research to translate findings into practical applications. The role requires strong ownership of the full project lifecycle and collaboration with business and engineering teams.

What you'd actually do

  1. Handle challenging problems that directly impact millions of selling partners
  2. Independently collect and analyze data
  3. Design, develop and deliver scalable models, using any necessary programming, machine learning, and statistical analysis software
  4. Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research
  5. Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software

Skills

Required

  • 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

Nice to have

  • 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.
  • Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
  • Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
  • Experience identifying opportunities to integrate AI solutions into products and services to drive business value

What the JD emphasized

  • building machine learning models for business application experience
  • building speech recognition, machine translation and natural language processing systems
  • building AI solutions into products and services

Other signals

  • Develop and implement advanced AI and machine learning solutions
  • Design, develop and deliver scalable models
  • Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications.