招聘
Fire TV Catalog powers the content discovery experience for tens of millions of customers worldwide. At its core, the catalog must answer a deceptively hard question: is this the same movie, show, game, or clip across dozens of providers? The Matching team owns entity resolution — the system that groups provider items referring to the same real-world content into unified clusters. This is what makes it possible for a customer to see a single tile for a movie with rent, buy, and subscription options from multiple services side by side, rather than a fragmented wall of duplicates.
Our matching pipeline processes tens-of-millions of records incrementally across single-host and distributed architectures, maintaining low end-to-end latency while handling complex deduplication across hundreds of content providers. We already leverage LLMs in production for match inference — using large language models to reason about whether two items represent the same content in cases where traditional signals are ambiguous or insufficient. As Fire TV expands into short-form video, live sports, and new entity types, the matching problem is evolving — traditional title/year/ID signals don't always apply, temporal and event-based matching introduces new dimensions, and the scale and diversity of content continues to grow.
A Senior SDE will be the technical leader for the Matching team. You will own the architecture and direction of our entity resolution systems, and you'll be expected to lead by example in leveraging AI — both as a tool for accelerating your own development and as a core component of the systems you build. This means using AI-assisted coding tools to move faster, while also pushing the boundaries of how LLMs and ML models can improve match quality in production.
- Key job responsibilities
- Designing and evolving matching algorithms that combine ML scoring, LLM-based inference, deterministic rules, external ID linking, and guard rails to produce high-precision clusters at catalog scale
- Expanding and improving our production use of LLMs for match decisions — optimizing prompt strategies, evaluating model performance, managing cost/latency trade-offs, and identifying new areas where LLM reasoning can replace or augment heuristic logic
- Driving the expansion of matching capabilities to new content types (short-form, sports events, live content) where existing signals and heuristics break down
- Owning the end-to-end quality of match decisions — precision, recall, and the customer-visible impact of getting it wrong (merged content that shouldn't be, or duplicates that persist)
- Leading technical design, code reviews, and operational excellence for a team of engineers
- Championing AI-assisted development practices across the team — setting the standard for how engineers use AI tools to write, review, test, and debug code more effectively
- Partnering with ingestion, curation, and publication teams to ensure matching integrates cleanly into the broader catalog pipeline
- Defining metrics, monitoring, and debugging tools that make match quality observable and actionable
Basic Qualifications
- 5+ years of non-internship professional software development experience
- 4+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
Preferred Qualifications
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually
总浏览量
0
申请点击数
0
模拟申请者数
0
收藏
0
相似职位

Senior End to End Performance Engineer
Apple · Seattle, WA

Sr Software Engineer
Walt Disney · Seattle, WA, USA

Principal Software Engineer, Loans Originations
SoFi · Seattle, Washington

Senior Software Engineer in Test - Test Platform
Apple · Seattle, WA

Senior Software Engineer - Forge Factory Automation
Anduril · Seattle, Washington, United States
关于Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
员工数
Seattle
总部位置
$1.5T
企业估值
评价
2.9
10条评价
工作生活平衡
2.8
薪酬
3.7
企业文化
2.5
职业发展
2.3
管理层
2.1
35%
推荐给朋友
优点
Good pay and compensation
Strong benefits package
Flexible scheduling options
缺点
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
薪资范围
4个数据点
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0份报告
$108,330
年薪总额
基本工资
$43,332
股票
$54,165
奖金
$10,833
$75,831
$140,829
面试经验
10次面试
难度
3.7
/ 5
时长
21-35周
录用率
20%
体验
正面 10%
中性 10%
负面 80%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
新闻动态
Amazon vs. Walmart: This Isn't Even Close - The Motley Fool
The Motley Fool
News
·
2d ago
'Kevin' Review: Jason Schwartzman, Aubrey Plaza in Amazon Cat Cartoon - The Hollywood Reporter
The Hollywood Reporter
News
·
2d ago
Amazon's best weekend deals: Apple, Clinique, Yeti and more — save up to 70% - Yahoo
Yahoo
News
·
2d ago
Amazon Delivery Drones Involve a Perilous 10-Foot Drop. Users Are Posting the Apparent Results - Gizmodo
Gizmodo
News
·
2d ago