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

Key job responsibilities

• 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.
• Develop scalable data processing pipelines and architectures to ingest, transform, and enrich Customer data from various sources (Retail, Prime Video, FireTV, Alexa+ and AppStore).
• 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.
• Drive innovation within your team and partner closely with other scientists, engineers and Product Managers to build science roadmaps
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
• Stay up-to-date with the latest advancements in machine learning, natural language processing, knowledge representation, multi-modal learning and related fields, and identify opportunities to apply them to Advertising Use Cases.
• We are looking for world class researchers with experience in one or more of the following areas of Agentic AI for ads targeting - autonomous agents, multi agent orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.
• Effectively communicate complex science problems and solutions to both technical and non-technical audiences.

About the team

This role is on Device Ads and Personalization (DAPP) team, which is under Amazon Publisher Monetization (APM). This team has a vision to create innovative Ad experiences on Amazon Devices, providing customers better convenience and more selection.

Basic Qualifications

• 5+ 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 in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)

Preferred Qualifications

• 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.