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트렌딩 기업

트렌딩 기업

채용

채용Amazon

SDE - ML & Risk Management Platforms, Core Services

Amazon

SDE - ML & Risk Management Platforms, Core Services

Amazon

Bengaluru, KA, IND

·

On-site

·

Full-time

·

1mo ago

필수 스킬

Machine Learning

Amazon.com's Risk Management Team has a worldwide reputation as the #1 in e Commerce Fraud Prevention. Trust and Safety of our customers comes first. Always. We thrive on maintaining the highest bar of customer experience while we maintain those tenets. Do you want to join a team that uses cutting edge technology including machine learning and statistical modeling techniques, cloud computing services and highly available and scalable distributed systems that supports hundreds of millions of transactions across the globe?
The Unified Risk Evaluation System team owns the charter of evaluating bad actor risk of all kinds (Buyer, Seller, Vendor) across entities such as Orders, Purchases, Signins and any event that will be useful to evaluate risky behavior. We process every single order and purchase in real time, totaling to more than 50 Billion evaluations in a year saving Billions of dollars that would otherwise be lost to bad actors. We build self-service capabilities to experiment new machine learning models and make it easy to onboard and manage 100s of risk use cases all over the world. We are the gate keepers of customer trust by preventing bad actors from doing damage to good customers or scamming Amazon. The problems we solve will challenge the best in terms of scale, ingenuity of bad actors and the cost of making risk decisions through bold goals we take such as automate 100% of risk decisions or reduce fraud and Abuse by 50% year over year.
Come join the best in class team of engineers, who are owners, and inventors. We are at the intersection of Machine Learning and Security, while delivering customer impact at amazon scale. Interact with ML scientists on a daily basis, and build the platform to beat to keep the bad guys out.

Basic Qualifications

  • 4+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language

Preferred Qualifications

  • 4+ 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

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.

총 조회수

0

총 지원 클릭 수

0

모의 지원자 수

0

스크랩

0

Amazon 소개

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+

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

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

0개 리포트

$181,968

총 연봉

기본급

-

주식

-

보너스

-

$154,672

$209,264

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