Applied Science Manager, Fire TV Science

Help re-invent how millions of people watch TV! Fire TV remains the #1 best-selling streaming media player in the US, with over 100 million active users. Our goal is to be the global leader in delivering entertainment, with the broadest selection of content, innovative devices, and personalized experiences for customers.

Our Fire TV Science team is an interdisciplinary group working at the intersection of Language Understanding (LU), Recommender Systems, Information Retrieval, and Machine Learning (ML). Through close collaboration with engineering and product teams, we develop and deploy innovative algorithms that enhance content discovery and customer engagement. Within this team, our Language Understanding sub-team owns all query understanding components and models that power search and content discovery on Fire TV. Our work directly contributes to making our devices delightful to use and indispensable for the household.

Key job responsibilities
- Be a hands-on lead for our Language Understanding (LU) sub-team, owning all our query understanding components and models

- Lead and mentor a team of 6 scientists, fostering their professional development and technical growth while establishing and executing the research vision

- Collaborate closely with Search and Recommendations workstreams within the broader Fire TV Science team, contributing to cross-functional initiatives and expanding technical influence beyond the LU domain

- Drive end-to-end impact by designing scalable solutions that systematically address technical challenges and deliver lasting customer benefit

- Balance and prioritize multiple workstreams spanning long-term research, applied projects, and production support to ensure high-impact outcomes

- Drive adoption of state-of-the-art approaches across the organization by staying at the forefront of relevant technological advances, spanning language understanding models, LLM evaluations, prompt engineering, search and personalization models, and more


A day in the life
As the Language Understanding sub-team lead, you'll balance hands-on technical work with team leadership and cross-functional collaboration. Your day might include conducting and reviewing model evaluations, interfacing with the Alexa central team on LLM routing and architectural design questions, resolving domain conflicts, and brainstorming with Search and Recommendations leads to explore synergies. You'll dive into code to prototype novel query understanding approaches, prioritize production issues, and engage with engineering and product partners on upcoming features. Throughout, you'll challenge the status quo, identify automation opportunities to free time for higher-impact work, and stay current with NLU research. The role involves regular travel between our two sites.

BASIC QUALIFICATIONS

- 4+ years of scientists or machine learning engineers management experience
- Knowledge of ML, NLP, Information Retrieval and Analytics
- PhD

PREFERRED QUALIFICATIONS

- Experience building machine learning models or developing algorithms for business application
- Knowledge of deep learning, machine learning and statistics
- Experience delivering results for large, cross-functional initiatives/projects
- Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track
- Experience effectively communicating complex concepts through written and verbal communication
- Experience leveraging GenAI techniques and models to solve technical business problems

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.

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