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求人Amazon

Applied Scientist, Grocery, Retail & In-Store Experience (GRAISE)

Amazon

Applied Scientist, Grocery, Retail & In-Store Experience (GRAISE)

Amazon

Seattle, WA, USA

·

On-site

·

Full-time

·

1mo ago

必須スキル

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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スクラップ

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Amazonについて

Amazon

Amazon

Public

Amazon.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

2.9

10件のレビュー

ワークライフバランス

2.8

報酬

3.7

企業文化

2.5

キャリア

2.3

経営陣

2.1

35%

友人に勧める

良い点

Good pay and compensation

Strong benefits package

Flexible scheduling options

改善点

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

給与レンジ

4件のデータ

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0件のレポート

$108,330

年収総額

基本給

$43,332

ストック

$54,165

ボーナス

$10,833

$75,831

$140,829

面接体験

10件の面接

難易度

3.7

/ 5

期間

21-35週間

内定率

20%

体験

ポジティブ 10%

普通 10%

ネガティブ 80%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge