Senior Applied Scientist, Sponsored Products and Brands -- Offsite

Amazon Amazon · Big Tech · NY +1 · Machine Learning Science

Senior Applied Scientist role focused on building and launching end-to-end AI solutions for Sponsored Products and Brands, specifically extending campaigns beyond the Amazon store to third-party environments. The role involves designing and implementing large-scale, low-latency systems using advanced ML and AI, conducting A/B experiments, and identifying opportunities for GenAI acceleration. It also includes defining science vision, mentoring junior scientists, and staying updated on the latest modeling techniques.

What you'd actually do

  1. Drive or heavily influence the design of scientifically-complex software solutions or systems. You take ownership of these components, providing a system-wide view and design guidance. These systems or solutions can be brand new or evolve from existing ones.
  2. Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end.
  3. Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses.
  4. Identify opportunities where GenAI solutions can accelerate learning and efficiency, and drive greater advertiser outcomes.
  5. Mentor and guide junior scientists, fostering a collaborative and high-performing team culture.

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.

What the JD emphasized

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

Other signals

  • Generative AI
  • Machine Learning
  • Large-scale systems
  • Low-latency systems
  • A/B experiments