Sr. Applied Scientist, Amazon Ads

Job summary

DESCRIPTION Amazon Ads is re-imagining advertising through generative artificial intelligence (AI) technologies. We combine human creativity with AI to transform every aspect of the advertising life cycle, from ad creation and optimization to performance analysis and customer insights.

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 with neural deep learning methods and machine learning
• PREFERRED
• Experience with modeling

Responsibilities

• As a Senior Applied Scientist in Amazon Ads, you will:
• Conduct hands-on data analysis, build large-scale machine-learning models and pipelines
• Build ML models, perform proof-of-concept, experiment, optimize, and deploy your models into production, working closely with cross-functional teams including engineers, product managers, and other scientists
• Design and run A/B experiments to validate hypotheses, gather insights from large-scale data analysis, and measure business impact.
• Research and implement ML approaches, including applications of generative AI and large language models.
• Drive end-to-end optimization projects that tackle ambiguous problems at massive scale, often working with petabytes of data.
• Provide technical leadership, research new machine learning approaches to drive continued scientific innovation
• Build supply optimization models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
• Develop scalable, efficient processes for model development, validation, and deployment that optimize traffic monetization while maintaining customer experience
• Criminal history may have a direct, adverse, and negative relationship with some of the material job
• of this position.
• These include the

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