채용

Applied Scientist, Grocery, Retail & In-Store Experience (GRAISE)
Seattle, WA, USA
·
On-site
·
Full-time
·
1mo ago
필수 스킬
Machine Learning
The GRAISE team (Grocery, Retail & In-Store Experience) within Worldwide Grocery Store Tech (WWGST) builds foundational AI and machine learning systems that power Amazon's in-store grocery technologies. We develop domain-specific models that solve uniquely complex challenges in grocery — from smart shopping carts and inventory intelligence to personalization and store operations. Our mission is to create technology which makes grocery shopping more convenient, economical, personalized, and enjoyable for customers while empowering retailers with operational efficiency.
We are looking for a talented and motivated Applied Scientist to join our team. In this role, you will design, develop, and deploy machine learning and computer vision models and algorithms that solve real-world problems at scale. You will work closely with engineering, product, and business teams to translate ambiguous problems into rigorous scientific solutions, and you will own the end-to-end development of models from ideation through production. This is a high-impact role where your work will directly shape the intelligence layer of Amazon's grocery ecosystem.
- Key job responsibilities
- Design and implement machine learning models to solve complex grocery-domain problems.
- Conduct exploratory data analysis and develop deep understanding of domain-specific data challenges.
- Collaborate with software engineers to productionize models and ensure reliability at scale.
- Define and track key metrics to evaluate model performance and business impact.
- Communicate findings and recommendations clearly to technical and non-technical stakeholders.
- Stay current with the latest research and evaluate applicability to team problems.
- Contribute to a culture of scientific rigor, experimentation, and continuous improvement.
A day in the life
As an Applied Scientist on the GRAISE team, you'll spend your days analyzing model performance from overnight experiments, collaborating with engineers to deploy computer vision models to production, and prototyping new approaches using multimodal learning with store video and sensor data. You'll present findings to product and business stakeholders, translating technical results into actionable recommendations. Throughout the day, you'll balance rigorous scientific thinking with practical engineering constraints, knowing your work directly improves the shopping experience for millions of customers in Amazon grocery stores.
Basic Qualifications
- PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience
- 2+ years of building machine learning models or developing algorithms for business application experience
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience with popular deep learning frameworks such as Mx Net and Tensor Flow
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
Preferred Qualifications
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience with programming languages such as Python, Java, C++
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 - 142,800.00 - 193,200.00 USD annually
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Amazon 소개

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+
직원 수
Seattle
본사 위치
$1.5T
기업 가치
리뷰
2.9
10개 리뷰
워라밸
2.8
보상
3.7
문화
2.5
커리어
2.3
경영진
2.1
35%
친구에게 추천
장점
Good pay and compensation
Strong benefits package
Flexible scheduling options
단점
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
연봉 정보
4개 데이터
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0개 리포트
$108,330
총 연봉
기본급
$43,332
주식
$54,165
보너스
$10,833
$75,831
$140,829
면접 경험
10개 면접
난이도
3.7
/ 5
소요 기간
21-35주
합격률
20%
경험
긍정 10%
보통 10%
부정 80%
면접 과정
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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