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Agentic AI Teacher (Fixed term contract)

Amazon

Agentic AI Teacher (Fixed term contract)

Amazon

Chennai, TN, IND

·

On-site

·

Contract

·

1mo ago

Benefits & Perks

Healthcare

401(k)

Equity

Healthcare

401k

Equity

Required Skills

Data annotation

Written communication

Amazon is investing in generative AI and the responsible development and deployment of Large Language Models (LLMs) across all our businesses. As part of the Data Team, you will deliver high-quality training data to improve and expand our proprietary LLM capabilities. We seek innovative candidates who can solve complex problems and drive technological advancement in AI. Your work will directly impact how Amazon's customers interact with our AI systems across multiple business lines.
This is a fixed term contractual role for 1 year, requiring flexibility to work in rotational shifts.

Key job responsibilities

  • Create and annotate high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content
  • Write grammatically correct texts in different styles with various degrees of creativity, strictly adhering to provided guidelines
  • Interpret technical documentation to implement solutions accurately
  • Dive deep into issues and implement solutions independently
  • Identify and report tooling bugs and suggest improvements
  • Make sound judgments and logical decisions when faced with ambiguous or incomplete information

About the team
Amazon strives to be the world’s most customer-centric company, where customers can research and purchase anything they might want online or offline. We set big goals and are looking for people who can help us reach and exceed them. The AGI organization provides AI capabilities for a variety of Amazon products and searches. We provide secure, flexible, cost effective, and high-quality data development services to our customers, that enables them to build advanced ML models.

Basic Qualifications

  • Bachelor's degree or equivalent
  • Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy
  • Familiarity with written language data, including experience with annotation, and other forms of data markup.

Preferred Qualifications

  • Advanced English-level language proficiency (C1+ or equivalent fluency by Common European Framework of Reference for Languages (CEFR) standards).
  • Utilize Python and SQL to automate and optimize data processing workflows
  • Experience/ability to learn and manage stakeholder relationships across departments

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

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 reports

$181,968

total / year

Base

-

Stock

-

Bonus

-

$154,672

$209,264

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