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Program Manager I, International Seller Growth

RoleProject Management
LevelLead
LocationShanghai, 31, CHN
WorkOn-site
TypeFull-time
Posted2 weeks ago
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The Seller AI team within International Seller Services organization is focused on helping sellers with the right set of Gen-AI/LLM powered tools and agentic solutions that can enable them to accelerate business growth on Amazon. Our primary focus lies in handling annotations for training, measuring, and improving Artificial Intelligence (AI) and Large Language Models (LLMs), enabling Amazon to deliver a superior seller experience to our sellers worldwide. The AI Benchmarking Associate supports the evaluation of AI systems by designing and executing benchmarking and audit activities to assess model quality, compliance, robustness, and fairness. The role combines elements of AI auditing, quality assurance, and traditional audit-style documentation and stakeholder communication. By joining us, you will play a pivotal role in shaping the future of selling on Amazon for sellers worldwide.

Key job responsibilities

  • As part of your role, you will have the opportunity to,
  • Assist in planning and executing benchmarking exercises for AI models, including defining test plans, metrics, and acceptance criteria across accuracy, robustness, bias, and reliability
  • Support content accuracy, relevancy, and privacy checks by reviewing datasets, model outputs, and data handling practices, escalating potential regulatory risks.
  • Validate data based on specific annotation guidelines, ensuring the accuracy and quality of the collected information
  • Prepare clear audit and benchmarking reports, including error ratings, root-cause analysis, and recommendations, and contribute to presentations for senior stakeholders
  • Maintain organized audit documentation, evidence, and benchmarking datasets to support internal review
  • You will work closely with your team members and managers to drive process efficiencies and explore opportunities for automation
  • You will strive to enhance the productivity and effectiveness of the data generation by contributing to the development and continuous improvement of AI audit methodologies, checklists, and test frameworks as regulations and best practices evolve

Basic Qualifications

  • 2+ years of program or project management experience
  • 3+ years of advanced Microsoft Word and Excel experience
  • Bachelor's degree in relevant field, or 2+ years of Amazon RME (BB/3P) full time experience

Preferred Qualifications

  • Experience working in an analytical environment with cross-functional teams
  • Experience with AI/ML technologies

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

$1.5T

Valuation

Reviews

10 reviews

3.4

10 reviews

Work-life balance

2.5

Compensation

4.2

Culture

3.0

Career

3.8

Management

2.7

65%

Recommend to a friend

Pros

Great benefits and competitive pay

Learning and advancement opportunities

Good teamwork and colleagues

Cons

High pressure and long hours

Poor work-life balance

Toxic work culture and management issues

Salary Ranges

4 data points

Junior/L3

M3

M4

M5

M6

Mid/L4

Senior/L5

Staff/L6

VP

Director

Junior/L3 · Product Manager L5

0 reports

$187,921

total per year

Base

-

Stock

-

Bonus

-

$159,732

$216,110

Interview experience

6 interviews

Difficulty

4.0

/ 5

Duration

21-35 weeks

Experience

Positive 0%

Neutral 17%

Negative 83%

Interview process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Technical Interview

6

Onsite/Virtual Interviews

Common questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge