Senior Applied Scientist, Amazon

• Demonstrated ability to meet deadlines while managing multiple projects
• Excellent communication and presentation skills working with multiple peer groups and different levels of management
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning
• Experience in building machine learning models for business application
• Experience in applied research
• PhD in ML and 5+ year of industry experience

Desirable

• Amazon Advertising is looking for a Senior Applied Scientist to join its brand new initiative that powers Amazon’s Brand Safety product
• We are looking for a dynamic, innovative, and accomplished Senior Applied Scientist to work on machine learning initiatives that power our brand safety solutions
• The role requires developing and fine-tuning Large Language Models at scale, designing content filtering systems, implementing alignment techniques, and creating robust evaluation frameworks to ensure AI outputs meet strict quality standards
• As a Senior Applied Scientist, you will own business problems of high ambiguity where you get to define the path forward for success of how we evolve our Brand Safety solutions
• You will get an opportunity to act as a thought leader, work backwards from customer needs, dive deep into data to understand the issues, conceptualize and build algorithms, and collaborate with multiple cross-functional teams
• 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
• Influence and continuously improve a sustainable team culture that exemplifies Amazon’s leadership principles
• The Supply Quality organization has the charter to solve optimization problems for ad-programs in Amazon and ensure high-quality ad-impressions
• We develop advanced algorithms and infrastructure systems to optimize performance for our advertisers and publishers
• We are focused on solving a wide variety of problems in computational advertising like Contextual data processing and classification, traffic quality prediction (robot and fraud detection), Security forensics and research, Viewability prediction, Brand Safety and experimentation
• Our team includes experts in the areas of distributed computing, machine learning, statistics, optimization, text mining, information theory and big data systems