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Mechanical Process Engineer Intern, 2026 Internship, Shenzhen, China

Amazon

Mechanical Process Engineer Intern, 2026 Internship, Shenzhen, China

Amazon

Shenzhen, 44, CHN

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

401(k) matching

Professional development budget

Team events and activities

Competitive salary and equity package

Learning

Equity

Required Skills

Python

JavaScript

TypeScript

请注意,申请此实习岗位需要满足如下条件:
毕业时间:26年12月至27年9月之间毕业
面试时间:26年1月开始
入职日期:26年5-6月
实习时间:暑期全职实习,至少持续3个月
工作地点:深圳市福田区,深圳国际创新中心B座
简历要求:请提供中英双语简历(放在一个文件中)
投递须知:
1 填写简历申请时,请把必填和非必填项都填写完整。提交简历之后就无法修改了哦!
2 学校的英文全称请准确填写。
3 校招信息请参考校园招聘申请手册:https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e
Amazon is an inventive research and development company that designs and engineers’ high-profile, consumer electronics products, like the Kindle, Kindle Fire, Fire TV and Echo, etc. The products we design and engineer are easy-to-use and offer users benefits that are only made possible through tightly integrated digital technologies and wireless connectivity.
The Mechanical Process Engineer (MPE) Intern works closely with teams located in both the US and China throughout the design cycle. As a member of the MPE team, you will assist the driving of mechanical part manufacturing and decorative processes. You will assist a Senior MPE in closely monitoring and reporting open manufacturing issues in the supply base.

  • Key job responsibilities
  • Work closely with Senior MPE team members in supplier monitoring and reporting open issues
  • Participate in the review and development of part/sub-assembly process flow, including process fixture concept and DFM
  • Assist in the organization of technical data documentation throughout the development cycle including FAI, CMK, CPK, GR&R, and DFM
  • Travel domestically and internationally to sites as projects required
  • Can work 5 days per week during summer holiday for at least 3 months duration
  • Is willing to work in Shenzhen

Basic Qualifications

  • Speak, write, and read fluently in Mandarin
  • Enrolled in a Bachelor’s or above degree program in Mechanical Engineering, Material Processing or related field.
  • Candidates must be in their pre-final year of Bachelor or Master Course

Preferred Qualifications

  • Knowledge of manufacturing processes of plastic or metal parts
  • Knowledge of production process qualification, measurement, and analysis
  • Familiar with CAD software
  • Strong organizational and problem-solving skills
  • Clear oral and written communication skills (Chinese and English)
  • Demonstrated critical thinking capability
  • Self-motivated and proactive
  • Previous internship experience
  • Past experience or coursework with statistical analysis and processing tools such as Minitab
    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.

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About Amazon

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+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0 reports

$108,330

total / year

Base

$43,332

Stock

$54,165

Bonus

$10,833

$75,831

$140,829

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge