refresh

トレンド企業

Trending

採用

JobsAmazon

Applied Scientist II, Selection Monitoring, Selection Monitoring

Amazon

Applied Scientist II, Selection Monitoring, Selection Monitoring

Amazon

Bengaluru, KA, IND

·

On-site

·

Full-time

·

3w ago

Benefits & Perks

Healthcare

401(k)

Equity

Parental Leave

Healthcare

401k

Equity

Parental Leave

Required Skills

Machine Learning

Python

Java

C++

NLP

Deep Learning

Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we develop advanced ML/AI technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing.

The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from research, prototype, design, coding and deployment. We are looking for Applied Scientists to tackle challenging problems in the areas of Information Extraction, Efficient crawling at internet scale, developing models for website comprehension and agents to take multi-step decisions. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and advanced machine learning. You should also have programming and design skills to manipulate Semi-Structured and unstructured data and systems that work at internet scale.

You will encounter many challenges, including:

  • Scale (build models to handle billions of pages),

  • Accuracy (requirements for precision and recall)

  • Speed (generate predictions for millions of new or changed pages with low latency)

  • Diversity (models need to work across different languages, market places and data sources)

  • You will help us to

  • Build a scalable system which can algorithmically extract information information from world wide web.

  • Intelligently cluster web pages, segment and classify regions, extract relevant information and structure the data available on semi-structured web.

  • Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents.

Key job responsibilities:

  • Use AI, NLP and advances in LLMs/SLMs and agentic systems to create scalable solutions for business problems.
  • Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes.
  • Design, develop, evaluate and deploy, innovative and highly scalable ML models.
  • Work closely with software engineering teams to drive real-time model implementations.
  • Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance.
  • Lead projects and mentor other scientists, engineers in the use of ML techniques.
  • Publish innovation in research forums.

Basic qualifications:

  • 3+ years experience building ML models for business application.
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
  • Experience programming in Python, Java, C++ or related languages.
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed
    computing, high-performance computing.

Preferred qualifications:

  • Experience using Unix/Linux.
  • Experience in professional software development.
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals.
  • Master's degree or above in computer science, computer engineering, or related field.

Basic Qualifications

  • 3+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience programming in Java, C++, Python or related language
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred Qualifications

  • Experience using Unix/Linux
  • Experience in professional software development

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.

Total Views

0

Apply Clicks

0

Mock Applicants

0

Scraps

0

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