Director, Applied Science, Alexa for Shopping (Rufus)

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

We are building the future of AI-powered commerce, where every customer interaction is conversational, personalized, and proactive.

Skills

• Deep expertise in large language models, post-training techniques (RLHF, fine-tuning, distillation), and/or multi-agent systems

Benefits

• Comprehensive benefits including health insurance, 401(k) matching, paid time off, and parental leave

Pay

Base salary range: $262,500.00 - $350,000.00 USD annually

Schedule

Not specified