Sr. Applied Scientist, Amazon Personalization - Customer 360

We're looking for a senior scientist to lead the research direction for a system that gives AI persistent, compounding memory. This is a new problem space — not recommendation, not search, not summarization, though it draws from all three. The right scientist will define what this field becomes.

Responsibilities

• Own the scientific roadmap for personalization initiatives, identifying high-impact research directions and translating ambiguous problems into well-defined ML formulations.
• Lead end-to-end systems spanning knowledge acquisition, retrieval, and reasoning.
• Define the scientific roadmap for knowledge acquisition, representation, and retrieval at organizational scale.
• Lead research on how AI systems should learn from experience — what to capture, how to generalize, when to forget.
• Design evaluation frameworks for a system where "quality" means something new — right knowledge, right context, right confidence level.
• Own end-to-end research from problem formulation through production impact measurement.
• Mentor Applied Scientists and establish scientific standards for a new team.
• Partner with engineering leadership to translate research into architecture decisions that shape the product.
• Drive technical decisions on model architecture, training methodology, and evaluation frameworks, balancing scientific rigor with business impact.
• Publish at top-tier venues and advance the state of the art in applied knowledge systems.

About The Team

Born out of Amazon's Personalization organization, which pioneered personalization at internet scale. We're applying deep expertise in large-scale ML to a fundamentally new domain where the signal space, objective functions, and evaluation criteria are all open research questions. The team values innovation and offers a safe place to try, fail, and learn while fostering a culture of continuous improvement. Everyone is a leader and owner for everything we do as a team. We offer creative space with an entrepreneurial work environment focusing on customer obsession.

Requirements

• 4+ years of applied research experience.
• 3+ 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.

Pay

USA, WA, Seattle - $167,100.00 - $226,100.00 USD annually.

Benefits

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