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ML Data Associate-II

Amazon

ML Data Associate-II

Amazon

Chennai, TN, IND

·

On-site

·

Full-time

·

1w ago

AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. Amazon is investing in generative AI and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us.

We are looking for those candidates who just don’t think out of the box, but make the box they are in ‘Bigger’. The future is now, do you want to be a part of it? Then read on!

  • Key job responsibilities
  • Maintain and follow strict confidentiality as customer privacy is our most important tenet
  • Work with a range of different types of data including, but not limited to: text, speech, audio, image, and video
  • Deliver high-quality labelled data, using guidelines provided to meet our KPIs and using in-house tools and software, as part of Amazon's commitment to developing and deploying AI responsibly.
  • Demonstrate proficiency in generating high quality human insight data across a range of modalities, inclusive of text, image video and audio.
  • Capable of making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks.
  • Eye for detail and ability to pivot from one category of requirement to another instantaneously.
  • Demonstrate support on daily operational deliverables for multiple task types assigned to you and the team
  • Analyze root causes, identify error patterns, and propose solutions to enhance the quality of labeling tasks and their outputs.
  • Responsible for identifying day-to-day process and operational issues in Standard Operating Procedure, tools and suggest changes to unblock operations
  • Demonstrate ownership in floor support to clarify internal queries during execution on need basis

A day in the life
We are looking for a ML Data Associate (MLDA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech, text, audio, video data.

Your ability to concentrate, multi-task and your high attention to detail helps you deliver high-quality work as well as maintaining strict confidentiality and follow all applicable Amazon policies for securing confidential information. You will be a part of a diverse team with the shared vision of improving customers’ lives with practical, useful generative AI innovations. An inner drive, individuality, and a creative mind are extremely beneficial.

Basic Qualifications

  • Experience in natural language data labeling, data annotation, linguistic annotation or other forms of data markup

Preferred Qualifications

  • Bachelor's degree 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.

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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

M3

M4

M5

M6

Intern

L2 · Revenue Operations L2

0 reports

$163,421

total / year

Base

$65,368

Stock

$81,711

Bonus

$16,342

$114,395

$212,447

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