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求人Amazon

Applied Scientist, Workplace Health & Safety

Amazon

Applied Scientist, Workplace Health & Safety

Amazon

Bellevue, WA, USA

·

On-site

·

Full-time

·

3w ago

必須スキル

Machine Learning

Are you driven by the challenge of solving complex problems that directly impact the safety and well-being of millions of Amazon Associates worldwide? Do you want to push the boundaries of AI to build innovative solutions that make workplaces safer and more efficient? If so, we invite you to join our WHS Data Tech team as an Applied Scientist and take your career to the next level!
At WHS Data Tech, we leverage Large Language Models (LLMs), Computer Vision, and AI-driven innovations to develop industry-leading solutions that proactively enhance workplace safety. Our work spans real-time risk assessment, predictive analytics, and AI-powered insights, all aimed at creating a safer work environment at scale.

As an Applied Scientist specializing in LLMs and Computer Vision, you will play a pivotal role in shaping our next-generation safety solutions. You’ll be at the forefront of innovation, designing and implementing AI-powered features that redefine workplace safety. Your work will drive strategic decisions, optimize system architecture, and influence best practices, ensuring our technology remains industry-leading.

  • Key job responsibilities
  • Apply LLM model to analyze complex unstructured datasets and extract meaningful insights.
  • Collaborate with software engineers to implement and deploy machine learning (LLM or CV) solutions.
  • Conduct experiments and evaluate model performance, iterating and improving as needed.
  • Stay up-to-date with the latest advancements in machine learning and related fields.
  • Collaborate with cross-functional teams to understand business needs and identify areas for application of machine learning.
  • Present findings and recommendations to stakeholders and contribute to the overall research and development strategy.

A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:

  1. Medical, Dental, and Vision Coverage

Maternity and Parental Leave Options:

  1. Paid Time Off (PTO)
  2. 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

About the team
WHS Data Tech is a multidisciplinary team of scientists and engineers dedicated to building AI-powered solutions that improve workplace safety across Amazon. We work at the intersection of large-scale data, advanced machine learning, and computer vision, delivering innovations that enhance decision-making, streamline operations, and protect millions of associates worldwide. Our collaborative culture emphasizes scientific rigor, engineering excellence, and a strong mission focus on creating safer, more efficient workplaces.

Basic Qualifications

  • Experience programming in Java, C++, Python or related language
  • Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

Preferred Qualifications

  • Experience implementing algorithms using both toolkits and self-developed code
  • Have publications at top-tier peer-reviewed conferences or journals

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, TN, Nashville - 136,000.00 - 184,000.00 USD annually
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually

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応募クリック数

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模擬応募者数

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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

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

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