Applied Scientist II, Amazon Search

We are seeking a talented applied researcher to join the Whole Page Planning and Optimization (WPPO) Science team in Search. The Search WPPO Science team is responsible for developing large-scale machine learning systems—spanning ranking, reinforcement learning, and large language models (LLMs)—that power the next generation Amazon shopping experience and deliver it to millions of customers. We believe that shopping on Amazon should be simple, delightful, and full of WOW moments for everyone, whether you are technically savvy or new to online shopping.

Responsibilities

• Work closely with a team of applied scientists and engineers to build systems that shape the future of Amazon's shopping experience by generating relevant content with LLMs and assembling a whole page experience that is coherent, dynamic, and interesting.
• Improve our ranking and optimization algorithms.
• Participate in driving features from idea to deployment, directly impacting millions of customers.
• Apply state-of-the-art Machine Learning (ML) algorithms, including Deep Learning, Reinforcement Learning, and Large Language Models (LLMs), to improve the shopping experience for hundreds of millions of customers.
• Have measurable business impact using A/B testing.
• Work in a dynamic team that provides continuous opportunities for learning and growth.
• Collaborate with leaders in the field of machine learning.

Requirements

• PhD, or Master's degree and 4+ years of CS, CE, ML, or related field experience.
• Experience programming in Java, C++, Python, or related language.
• 1+ years of building machine learning models or developing algorithms for business applications.
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.

Preferred Qualifications

• 1+ years of building production software experience.
• Ph.D. in computer science, mathematics, statistics, machine learning, or equivalent quantitative field.
• Experience in written and verbal communication with the ability to present complex technical information clearly and concisely to executives and non-technical leaders.
• At least 2 years of experience with predictive modeling and analysis, applying various machine learning techniques including supervised/unsupervised learning, deep learning, and reinforcement learning.
• Strong publication record at top ML conferences and journals.

Benefits

• Comprehensive health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, and optional supplemental life plans).
• Employee Assistance Program (EAP) and Mental Health Support.
• Medical Advice Line and Flexible Spending Accounts.
• Adoption and Surrogacy Reimbursement coverage.
• 401(k) matching.
• Paid time off and parental leave.
• Sign-on payments and restricted stock units (RSUs).

Pay

USA, WA, Seattle - $142,800.00 - $193,200.00 USD annually.