Applied Science Manager, Fire TV Science

Amazon • Sunnyvale, CA

41d

About The Position

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.

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.

Requirements

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

Nice To Haves

• 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

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

Benefits

• 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 [https://www.aboutamazon.com/workplace/employee-benefits].

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: Ph.D. or professional degree