Director, Applied Science, Alexa for Shopping (Rufus)

Description

Alexa for Shopping (Rufus) is Amazon's new AI-powered shopping assistant that combines the capabilities of Rufus and Alexa+. We are building the future of AI-powered commerce, where every customer interaction is conversational, personalized, and proactive.

Key job responsibilities

• Define and execute the science strategy for Alexa for Shopping conversational AI platform
• Lead a large, multidisciplinary organization of Applied Scientists, Research Scientists, and Machine Learning Engineers
• Architect and scale multi-agent systems
• Partner with Product, Engineering, and senior leadership (including S-team) to align AI investments with long-term business goals and the vision of conversational commerce replacing traditional shopping paradigms
• Establish scientific best practices across experimentation, evaluation, model iteration, and production deployment for a high-traffic, latency-sensitive customer-facing system
• Mentor and develop senior technical leaders; foster a culture of innovation, customer obsession, and operational excellence

Basic Qualifications

• MS in Computer Science, Machine Learning, Statistics, Operations Research, or related quantitative field
• 12+ years in applied machine learning and AI
• 10+ years of people management experience, including experience as a leader of leaders managing multiple science and/or engineering teams
• Demonstrated track record of building and shipping production AI/ML systems at scale with direct, measurable customer impact

Preferred Qualifications

• Ph.D. in Computer Science, Machine Learning, Statistics, Operations Research, or related quantitative field
• Deep expertise in large language models, post-training techniques (RLHF, fine-tuning, distillation), and/or multi-agent systems
• Experience defining and executing science strategy for organizations operating at the intersection of research innovation and product delivery
• Strong publication record or demonstrated thought leadership in relevant areas (LLMs, NLP, RL, conversational AI, recommendation systems)
• Excellent verbal and written communication skills with the ability to influence senior executives and translate complex technical concepts for business audiences
• Deep technical judgment combined with business acumen — ability to make tradeoffs across quality, latency, cost, and customer experience

About the role

The ideal candidate is deeply steeped in LLM-based architectures, post-training techniques (RLHF, fine-tuning, distillation), and multi-agent systems. They are passionate about applied science, working back from customer experience to define what matters, and building teams that ship production AI at scale. This leader will shape the science philosophy for one of Amazon's highest-visibility AI initiatives.

Pay

Base salary range: $297,500.00 - $350,000.00 USD annually

Schedule

Location: USA, CA, Palo Alto - 297,500.00 - 350,000.00 USD annually
USA, WA, Seattle - 262,500.00 - 350,000.00 USD annually