Sr. Applied Scientist, Amazon Ads
Description
Amazon Ads is re-imagining advertising through cutting-edge 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. Our solutions help advertisers grow their brands while enabling millions of customers to discover and purchase products through delightful experiences. We deliver billions of ad impressions and millions of clicks daily, breaking fresh ground in product and technical innovations.
This role offers unprecedented breadth in ML applications and access to extensive computational resources and rich datasets that will enable you to build truly innovative solutions. You'll work on projects that span the full advertising life cycle, from sophisticated ranking algorithms and real-time bidding systems to creative optimization and measurement solutions. You'll work alongside talented engineers, scientists, and product leaders in a culture that encourages innovation, experimentation, and bias for action, and you’ll directly influence business strategy through your scientific expertise.
Why You’ll Love This Role
This role offers unparalleled opportunities for scientific innovation and real-world impact. You'll re-imagine advertising through the lens of advanced ML while solving problems that balance the needs of advertisers, customers, and Amazon's business objectives. Your work will directly impact millions, and you'll have clear paths for career progression, combining scientific leadership, organizational ability, technical strength, and business understanding.
Key job responsibilities
Research and implement cutting-edge ML approaches, including applications of generative AI and large language models.
Develop and deploy innovative ML solutions spanning multiple disciplines – from ranking and personalization to natural language processing, computer vision, recommender systems, and large language models.
Drive end-to-end projects that tackle ambiguous problems at massive scale, often working with petabytes of data.
Build and optimize models that balance multiple stakeholder needs - helping customers discover relevant products while enabling advertisers to achieve their goals efficiently.
Develop and optimize 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.
Create scalable, efficient processes for model development, validation, and deployment that optimize traffic monetization while maintaining customer experience.
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 with neural deep learning methods and machine learning
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.