
Work hard. Have fun. Make history.
Applied Scientist II, Trustworthy Shopping Experience (TSE)
Are you passionate about solving complex business problems at scale through Generative AI? Do you want to build intelligent systems that reason, act, and learn from minimal supervision? Are you excited about taking innovative AI solutions from proof-of-concept to production? If so, we have an exciting opportunity for you on Amazon's Trustworthy Shopping Experience (TSE) team.
At TSE, our vision is to guarantee customers a worry-free shopping experience by earning their trust that the products they buy are safe, authentic, and compliant with regulations and policy. We give customers confidence that Amazon stands behind every product and will make it right in the rare chance anything goes wrong. We do this in close partnership with our selling partners and empower them with best-in-class tools and expertise required to offer a high-quality selection of compliant products that customers trust.
As an Applied Scientist, you will lead the development of next Gen AI solutions to automate complex manual investigation processes at Amazon scale. You will work on some of the most fascinating challenges in applied AI—building systems that reason and act autonomously, learn rich representations from structured and relational data without extensive labels, adapt rapidly from limited examples, improve through feedback and interaction, seamlessly connect visual and textual understanding, and compress complex model capabilities into efficient, deployable systems. Your innovations will deliver significant impact to cost-of-serving customers while maintaining the highest standards of trust and safety.
This role offers end-to-end ownership—from initial research and proof-of-concept through production
deployment. You will see your innovations serving hundreds of millions of customers within months, not years.
- Key job responsibilities
- Design and build expertise agentic AI systems with multi-step reasoning, autonomous task execution, and multimodal intelligence with capabilities to handle feedback with memory mechanisms.
- Productionize large scale models built on top of SFT (Supervised Finetuning) and RFT (Reinforced fine tuning) approaches, few shot approaches based on multimodal datasets
- Build novel production ready Deep and conventional ML solutions to aid the multiple potential automation requirements
- Identify customer and business problems at project level; invent or extend state-of-the-art approaches for complex workflows involving unstructured text, documents, images, and relational data
- Author or co-author research papers for peer-reviewed venues; serve as PC member at conferences when aligned with business needs
- Prototype rapidly, iterate based on feedback, and deliver components at SDE I+ level that integrate directly into production-scale systems
- Engineer efficient systems balancing model capability, deployment cost, and resource usage; write significant code demonstrating technical excellence and maintainability
- Scrutinize algorithm and software performance for improvements; resolve root causes leaving systems more maintainable
- Contribute to tactical and strategic planning—team goals, priorities, and roadmaps—while providing architectural guidance for AI systems
- Participate in engineering best practices with rigorous peer reviews; communicate design decisions clearly and participate in science reviews
- Train new teammates on component construction and integration; mentor less experienced scientists and participate in hiring processes
About the team
Investigation technology Product team in TSE is responsible for the human-in-the-loop products and technology used in the risk investigations at Amazon. The team is also responsible for reducing the cost of performing the investigations, by automating wherever possible and optimizing the experience where manual interventions are needed. The team leverages state-of-the art technology and GenAI to deliver the products and associated goals.
Basic Qualifications
- 3+ years of building models for business application experience
- PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred Qualifications
- Experience using Unix/Linux
- Experience in professional software development
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.
閲覧数
0
応募クリック
0
Mock Apply
0
スクラップ
0
類似の求人
Amazonについて

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+
従業員数
Seattle
本社所在地
$1.5T
企業価値
レビュー
10件のレビュー
3.4
10件のレビュー
ワークライフバランス
2.5
報酬
4.2
企業文化
3.0
キャリア
3.8
経営陣
2.7
65%
知人への推奨率
良い点
Great benefits and competitive pay
Learning and advancement opportunities
Good teamwork and colleagues
改善点
High pressure and long hours
Poor work-life balance
Toxic work culture and management issues
給与レンジ
4件のデータ
Junior/L3
L2
L6
M3
M4
M5
M6
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
L3
L4
L5
Junior/L3 · Data Scientist L4
0件のレポート
$181,968
年収総額
基本給
-
ストック
-
ボーナス
-
$154,672
$209,264
面接レビュー
レビュー6件
難易度
4.0
/ 5
期間
21-35週間
体験
ポジティブ 0%
普通 17%
ネガティブ 83%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Technical Interview
6
Onsite/Virtual Interviews
よくある質問
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
最新情報
OpenAI’s subtle drift from Microsoft has become an aggressive move toward Amazon - CNBC
CNBC
News
·
1w ago
A blue-collar worker says he makes $10,000 per month from Amazon in just 20 hours of work — how you can do it, too - Yahoo Finance
Yahoo Finance
News
·
1w ago
Amazon Q1 earnings put the spotlight on AI spending and revenue - Yahoo Finance
Yahoo Finance
News
·
1w ago
Amazon Damage Claim NC | After delivery driver damages garage door, homeowner gets claims money: ABC11 Troubleshooter - ABC11 Raleigh-Durham
ABC11 Raleigh-Durham
News
·
1w ago



