• PhD, or a Master's degree and experience in CS, CE, ML or related field research
• Experience programming in Java, C++, Python or related language
• Experience in building machine learning models for business application
• Experience building machine learning models or developing algorithms for business application
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Desirable

• Amazon is re-imagining advertising. Amazon Ads operates at the intersection of eCommerce and advertising and offering a rich array of advertising solutions and audience insights so businesses and brands can create relevant campaigns that produce measurable results
• At Amazon Ads, you can build models that impact millions every day. And we’re passionate about solving real-world problems while using cutting-edge machine learning and artificial intelligence to do this
• For example, our applied science teams leverage a variety of advanced machine learning and cloud computing techniques to power Amazon's advertising offerings. This includes building algorithms and cloud services using clustering, deep neural networks, and other ML approaches to make ads more relevant while respecting privacy
• They develop machine learning models to predict ad outcomes and select the optimal ad for each shopper, context, and advertiser objective, leveraging techniques like multi-task learning, bandit/reinforcement learning, counterfactual estimation, and low-latency extreme ML
• The teams also utilize Spark, EMR, and Elasticsearch to extract insights from big data and deliver recommendations to advertisers at scale, continuously improving through offline analysis and impact evaluation
• Additionally, they apply generative AI models for dynamic creative optimization and video experimentation and automation
• Design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both analysis and business judgment
• Collaborate with software engineering teams to integrate successful experiments into large-scale, highly complex Amazon production systems
• Promote the culture of experimentation and applied science at Amazon
• Demonstrate ability to meet deadlines while managing multiple projects
• Excel communication and presentation skills working with multiple peer groups and different levels of management
• Influence and continuously improve a sustainable team culture that exemplifies Amazon’s leadership principles