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Professional Services II - AMZ18353.8

Amazon

Professional Services II - AMZ18353.8

Amazon

Dallas, TX, USA

·

On-site

·

Full-time

·

1mo ago

Compensation

$131,300 - $131,300

Benefits & Perks

Healthcare

401(k)

Healthcare

401k

Required Skills

Python

Machine Learning

Cloud Solutions

Generative AI

Employer: Amazon Web Services, Inc.
Position: Professional Services II AMZ18353.8
Location: Dallas, TX

Multiple Positions Available:

  1. Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
  2. Build robust and scalable Generative AI solutions for customer facing business problems
  3. Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
  4. Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
  5. Provide customer and market feedback to product and engineering teams to help define product direction
  6. Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes
  7. Domestic travel up to 25% to perform role responsibilities may be required

(40 hours / week, 8:00am-5:00pm, Salary Range $131,300/year to $177,600/year)

Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation

Basic Qualifications

Bachelor’s degree or foreign equivalent degree in Computer Science, Mathematics, or a related technical or scientific field followed by 5 years of progressively responsible post-baccalaureate experience in the job offered or a related occupation. In the alternative, employer will accept a Master’s degree or foreign equivalent degree in Computer Science, Mathematics, or a related technical or scientific field and 2 years of experience in the job offered or a related occupation.
Experience must include:

  1. 2 years of experience in designing, building, and/or operating cloud solutions in a production environment
  2. 2 years of experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
  3. 2 years of hands on experience with Python to build, train, and evaluate models
  4. 2 years of technical client engagement experience

Preferred Qualifications

All applicants must meet all the above listed requirements.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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