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Description

Passionate about creating visual customer experiences that push the boundaries at the forefront of GenAI?

The North America Stores GenAI Evaluation Media (GEM) team is seeking an experienced Applied Science Manager to help shape the future of visual shopping experiences. We're building CXs and foundational capabilities to understand, enhance, and generate real-time GenAI imagery, videos and CXs that inspire customers and drive purchase confidence, towards our vision to be the leader in visual media. Specifically, the charter will focus on visual agentic experiences, multi-modal personalization, vision language models, and real-time image/video generation, looking ahead as customer shopping continues to inspirational assistant-driven experiences.

The Applied Science Manager will lead a team of Applied Scientists and Machine Learning Engineers, and drive the technical vision and execution of agentic AI capabilities that inform and guide the customer’s shopping journey through visuals. This includes developing core science primitives for multimodal understanding, visual content generation and editing, personalized virtual try-on, and automated quality assurance. Your team will build the foundational capabilities that enable customers to express and discover styles through multimodal conversation and receive personalized, visual responses that bring their ideas to life. The scientific approach emphasizes accurate, real-time visual understanding and generation, contextual understanding, and scalable personalization, enabling agentic AI to actively collaborate with customers to achieve their style goals. Your team will bring together computer vision, natural language processing, generative AI, and human-centered design to create agentic shopping experiences that are as intuitive as talking to a human specialist with a deep domain knowledge base. Success requires establishing robust metrics, working with multiple partners in cross-team collaboration, validating asset effectiveness across diverse customer touch points, and navigating rapid advances in AI technology to maintain competitive advantage.

The ideal candidate will combine deep technical expertise in Computer Vision, Generative AI, or related fields with strong business acumen and strategic leadership skills. You will partner with stakeholders across Amazon to align priorities, drive innovation, and build a culture of scientific excellence and customer obsession. This role requires both strategic thinking and technical depth, with a focus on delivering practical solutions that scale. This is a unique opportunity to shape the future of visual commerce through applied AI research, leading a team that will define how hundreds of millions of customers discover and evaluate products and styles through visual experiences.

Key job responsibilities

Technical & Strategic Leadership

• Drive the technical vision and roadmap, aligning with business goals and customer needs

• Lead development of core science primitives for vision and language understanding, visual content generation and editing, virtual try-on, and automated quality assurance via state-of-art computer vision, machine learning, generative AI

• Design and implement visual agentic systems, balancing visual quality, relevance, latency, and cost

• Establish metrics and success criteria for scientific initiatives, ensuring rigorous validation across customer touch points

Team Leadership

• Lead and develop a high-performing team of Applied Scientists and Machine Learning Engineers

• Foster a culture of scientific excellence, innovation, and customer obsession

• Recruit and retain top talent in computer vision, machine learning, and generative AI

• Mentor and grow future technical leaders

• Partner with multiple teams within Amazon

• Facilitate learning and knowledge sharing within the team via presentations at internal and external science forums

Execution & Innovation

• Drive development and deployment of scalable agentic systems for visual content understanding and generation

• Own end-to-end delivery of multiple concurrent research initiatives

• Establish and maintain high scientific and engineering standards across the team

• Stay current with latest advances in ML/AI and identify opportunities to apply them

• Guide technical direction for complex problems while maintaining practical focus on customer value

Cross-functional Leadership

• Partner with product and engineering teams to deliver customer-facing features

• Drive alignment across teams on technical approaches and resource allocation

Basic Qualifications

- 3+ years of scientists or machine learning engineers management experience

- PhD in computer science, machine learning, engineering, or related fields, or Master's degree

- Experience hiring, developing, and managing high-performing technical teams

- Master's degree in related field with 8+ years of industry experience

- Experience building complex software systems, especially involving generative AI, machine learning and computer vision, that have been successfully delivered to customers

Preferred Qualifications

- Experience building machine learning models or developing algorithms for business application

- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers

- Experience in e-commerce, retail or advertising

- Experience understanding needs of business and end customers and translating them into right solutions

- Experience working effectively across cross-functional teams and partnering well with people at all levels within an organization

- Experience developing, deploying and managing AI products at scale

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $165,500/year in our lowest geographic market up to $286,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.