The Senior Manager, Applied Science owns the science mission for new GenAI products and initiatives across Alexa AI's Personalization, Autonomy and Proactive Intelligence organization, bringing together Personalization science to power Alexa experiences. You will lead a team of applied scientists to harness state of the art technologies across machine learning, natural language processing, LLM training, and application, to advance the scientific frontiers of AI personalization and autonomous intelligence. The right candidate will be an inventor at heart, provide deep scientific leadership, establish compelling technical direction and vision, and drive ambitious research initiatives that push the boundaries of what's possible with AI.
You will need to be adept at identifying promising research directions, developing novel AI solutions, and translating advanced AI research into production-ready models. You will need to be adept at influencing and collaborating with partner teams, launching AI models into production, and building team mechanisms that will foster innovation and execution. This role represents a unique opportunity to tackle fundamental challenges in how Alexa understands, personalizes, and proactively assists users through state-of-the-art AI technologies.
As a science leader in Alexa AI, you will shape the technical strategy for making Alexa more intuitive, autonomous, and personally relevant to customers through advanced AI capabilities. Your team will be at the forefront of solving complex problems in personalization, multimodal understanding, autonomous reasoning, and proactive intelligence that will fundamentally enhance how users interact with Alexa.
The successful candidate will bring deep technical expertise in machine learning and natural language processing, along with the leadership ability to guide talented scientists in pursuing ambitious research that advances the state of the art in AI-driven personalization.
Key job responsibilities
Technical Leadership
- Lead complex research and development projects
- Partner closely with the T&C Product and Engineering leaders on the technical strategy and roadmap
- Evaluate emerging technologies and methodologies
- Make high-level architectural decisions
Team Management
- Lead, mentor and develop technical talent
- Set team goals and performance metrics
- Manage resource allocation and project prioritization
Research & Development
- Drive innovation in applied science areas
- Translate research into practical business solutions
- Author technical papers and patents
- Collaborate with academic and industry partners
About the team
PAPI (Personalization Autonomy and Proactive Intelligence) aims to accelerate personalized and intuitive experiences across Amazon's customer touchpoints through automated, scalable, self-serve AI systems. We leverage customer, device, and ambient signals to deliver conversational, visual, and proactive experiences that delight customers, increase engagement, reduce defects, and enable natural interactions across Amazon touch points including Alexa, FireTV, and Mobile. Our systems offer personalized suggestions, comprehend customer inputs, learn from interactions, and propose appropriate actions to serve millions of customers globally. - M.S. in Computer Science, Machine Learning, or a related field.
- 10+ years experience in natural language processing, machine learning, recommendation, search, multimodal AI, or a related field.
- Proven track record of leading and managing science and engineering teams in building complex, real-time systems involving AI, ML, NLP with successful delivery to customers.
- Demonstrated track record of project delivery for large, cross-functional projects with evolving requirements. Ability to take a project from requirements gathering and design to actual product launch, customer validation and scaling.
- Exceptional customer relationship skills including the ability to discover the true requirements underlying feature requests, recommend alternative technical and business approaches, and lead combined science and engineering efforts to meet timelines with optimal solutions.
Preferred qualifications
- Ph.D. in Computer Science, Machine Learning, or a related field.
- 10+ years experience in recommendations, search, natural language processing, machine learning, deep learning, Generative AI, Agentic AI or a related field.
- Demonstrated ability to push the envelope in at least one machine learning domain (e.g. deep learning, NLP, reinforcement learning)
- Expertise in large language models or demonstrated ability to develop this expertise quickly.
- Excellent written and verbal technical communication with an ability to present complex technical information in a clear and concise manner to a variety of audience.
- Expertise in end-consumer AI experiences, ideally with learning/ experiential offerings.
- Demonstrated track record of peer-reviewed scientific publications that advance state-of-the art for applied science.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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 $196,900/year in our lowest geographic market up to $340,300/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.
