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Sr. SDE, Machine Learning, Prime Video Personalization and Discovery

Amazon

Sr. SDE, Machine Learning, Prime Video Personalization and Discovery

Amazon

Seattle, WA, USA

·

On-site

·

Full-time

·

1mo ago

Compensation

$168,100 - $227,400

Benefits & Perks

Healthcare

401(k)

Equity

Parental Leave

Mental Health

Healthcare

401k

Equity

Parental Leave

Mental Health

Required Skills

Software development

System design

Architecture design

Team leadership

Machine learning

Just finished “Rings of Power” or “Thursday Night Football” and want to find something new to stream? So do tens of millions of our Prime Video customers. The Prime Video Recommendation team's mission is to leverage Machine Learning (ML) systems that establish deep connections between customers and their favorite Movies, TV shows, and Live Events in order to power highly personalized recommendations, identify the most delightful content for each customer to engage with at the right time, in the right place, across Prime Video. We help our customers find content they didn’t even know they were looking for, continuing to surprise them with the breadth and depth of content available to enjoy.

  • Key job responsibilities
  • Building and operating services that deliver millions of recommendations per second
  • Driving innovation through continuous experimentation and use of state of the art ML solutions
  • Extending solutions to support constantly evolving landscape of Prime Video
  • Live Sports, Linear TV, etc.
  • Leading & Partnering on developing strategic technical vision for the PV Recommendations space.
  • Partnering with Product, Scientists and Engineering stakeholders

A day in the life
As Sr. SDE, you will be technical lead of an engineering team building services to deliver personalization solutions at incredible scale and speed. You will be operating with state of the art technologies on engineering and machine learning dimensions. Your responsibilities will include system design, prototyping new ML solutions, and planning A/B experimentation to demonstrate customer value of your solutions. You will foster a culture of innovation and excellence, leading and growing talented junior engineers on your team and around PV. At the end of the day, you will have the reward of seeing your contributions delight PV customers worldwide (including yourself!)

About the team
This team is at the heart of PV personalization - building ML-driven understanding about customers' preferences based on their past engagement, current context (e.g. device, title release date etc.) and other signals (e.g. search activity etc.). We use this understanding to power new video discovery experience across PV. We operate in a complex business/tech space requiring us to operate at speed and rapidly prototype/experiment. If you are excited about making an impact on a product that is used by 100M+ customers around the world, including your own friends and family, then this could be the right opportunity for you!

Basic Qualifications

  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience as a mentor, tech lead or leading an engineering team

Preferred Qualifications

  • 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent
  • Experience with training and deploying machine learning systems to solve large-scale optimizations

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually

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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