Applied Scientist III, Sponsored Products and Brands Auctions

About the role

The Search Ranking and Interleaving (R&I) team within Sponsored Products and Brands is responsible for determining which ads to show and the quality of ads shown on the search page. This includes relevance, personalization, and contextualization to improve the shopper experience, while also helping advertisers reach the right customers.

Responsibilities

• Identify big opportunities to improve the search experience for Amazon shoppers.
• Work closely with search and retail partner teams, software engineers, and product managers to build scalable real-time GenAI and ML solutions.
• Lead projects end-to-end, including problem formulation, model development, A/B experiment design and analysis.
• Architect next-generation systems that enhance Amazon's Search page.
• Pioneer breakthrough applied science in multi-modal GenAI applications for advertising, combining text, image, and multi-lingual support.
• Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions.
• Research new and innovative machine learning approaches.

Requirements

• 3+ years of building machine learning models for business applications.
• PhD or Master's degree with 6+ years of applied research experience.
• Experience programming in Java, C++, Python, or related languages.
• Experience with neural deep learning methods and machine learning.
• Experience with modeling tools like R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, etc.
• Experience with large-scale distributed systems like Hadoop, Spark.
• Experience in auctions or mechanism design.

Qualifications

• Basic Qualifications: 3+ years of building machine learning models for business applications, 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., Experience in auctions or mechanism design.

Skills

• 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.
• Experience in auctions or mechanism design.

Benefits

• Comprehensive benefits including medical, dental, vision, prescription, life insurance, AD&D, EAP, mental health support, medical advice line, flexible spending accounts, adoption and surrogacy reimbursement coverage.
• 401(k) matching.
• Paid time off.
• Parental leave.

Pay

The base salary range for this position is listed below. Final compensation will be determined based on factors including experience, qualifications, and location.

Schedule

Not specified.