Senior Applied Scientist, Entertainment Devices & Grocery Experiences (edge) Ads

Amazon Amazon · Big Tech · NY +1 · Applied Science

Senior Applied Scientist role focused on improving advertising performance and delivering innovative advertising experiences for Amazon devices and grocery. The role involves building and deploying machine learning models, with a specific emphasis on agentic AI for ads targeting, including autonomous agents, multi-agent orchestration, large multimodal models, reinforcement learning, and sequential decision making. The position requires experience in developing scalable data pipelines, optimizing conversion KPIs, and staying updated with the latest advancements in ML, NLP, and multimodal learning.

What you'd actually do

  1. Gain a comprehensive understanding of the customer lifecycle journey with Amazon Ads, and develop sophisticated models to optimize various conversion KPIs for enhanced marketing effectiveness.
  2. Develop scalable data processing pipelines and architectures to ingest, transform, and enrich Customer data from various sources (Retail, Prime Video, FireTV, Alexa+ and AppStore).
  3. Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with product managers and engineers to launch your models to customers.
  4. Drive innovation within your team and partner closely with other scientists, engineers and Product Managers to build science roadmaps
  5. Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.

Skills

Required

  • building machine learning models for business application experience
  • applied research experience
  • Java
  • C++
  • Python
  • machine learning
  • natural language processing
  • knowledge representation
  • multi-modal learning
  • autonomous agents
  • multi agent orchestration
  • Planning
  • large multimodal models
  • vision-language models
  • reinforcement learning (RL)
  • sequential decision making

Nice to have

  • R
  • scikit-learn
  • Spark MLLib
  • MxNet
  • Tensorflow
  • numpy
  • scipy
  • large scale distributed systems
  • Hadoop
  • Spark
  • speech recognition
  • machine translation

What the JD emphasized

  • agentic ai driven ads experience
  • autonomous agents
  • multi agent orchestration
  • large multimodal models
  • reinforcement learning (RL)
  • sequential decision making
  • building machine learning models for business application experience
  • PhD, or Master's degree and 6+ years of applied research experience

Other signals

  • improving advertising performance
  • delivering innovative advertising experiences
  • conversational ads
  • agentic ai driven ads experience
  • optimizing various conversion KPIs
  • build machine learning models
  • deploy your models into production
  • autonomous agents
  • multi agent orchestration
  • large multimodal models
  • reinforcement learning (RL)
  • sequential decision making