Sr. Applied Science Manager, AGI Information

The AGI Information organization is at the forefront of artificial intelligence and machine learning innovation, developing AI systems used across AWS, Alexa, and other Amazon businesses that transform how customers interact with information, in particular integrating a broad range of structured and unstructured information into AI systems (e.g. with RAG techniques). Our team combines world-class research with production-scale engineering to deliver impactful AI-driven products and services. We"re looking for an experienced leader who can drive scientific excellence while building and mentoring high-performing teams of applied scientists and machine learning engineers.

If you are deeply familiar with LLMs, natural language processing, and machine learning and have experience managing high-performing research teams, this may be the right opportunity for you. Our fast-paced environment requires a high degree of independence in making decisions and driving ambitious research agendas all the way to production. You will work with other science and engineering teams as well as business stakeholders to maximize velocity and impact of your team"s contributions.

It"s an exciting time to be a leader in AI research. In Amazon"s AGI Information team, you can make your mark by improving information-driven experience of Amazon customers worldwide!

Key job responsibilities

• Lead and manage teams of applied scientists and machine learning engineers, providing mentorship, career development, and performance management
• Define and execute the technical roadmap for applied science initiatives, balancing innovation with business impact
• Work with new technologies and methodologies that improve model performance, usability, and scalability of ML systems
• Translate complex business requirements into technical deliverables and deliver operationally stable solutions that provide exceptional customer experiences
• Participate in the full development cycle, end-to-end, from research and design to implementation, testing, documentation, delivery, and maintenance
• Evaluate and make strategic decisions around the use of new or existing ML frameworks, tools, and technologies
• Collaborate with Senior Engineers, Principal Engineers, and Principal Scientists across the organization to define architecture and research plans for the next three years
• Drive scientific rigor through experimentation, A/B testing, and data-driven decision making

Partner with cross-functional teams including product management, engineering, and business stakeholders to align science initiatives with business objectives

• Publish research findings and represent Amazon at top-tier conferences and in the scientific community
• Establish best practices for ML development, including model evaluation, monitoring, and continuous improvement