招聘

Engineering Manager, Experimentation Platform
USA - Remote; New York,New York,United States of America; Los Angeles,California,United States of America; Los Gatos,California,United States of America
·
Remote
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Full-time
·
1mo ago
At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
A culture of experimentation enables Netflix to continuously evolve and improve our products, delivering more joy to existing members and attracting new members from around the globe. Because experimentation is so pervasive at Netflix, we continually enable new capabilities and onboard new initiatives to the platform with close cross-functional collaboration with our Data Science partners.
At the nerve center of experimentation at Netflix is our internal, Netflix-wide, Experimentation Platform, responsible for democratizing trustworthy experiments across the company and enabling new capabilities across the company. We’re looking for 2 engineering managers to help lead the next generation of Experimentation Platform at Netflix.
Leadership opportunities
Experimentation Platform organizes into four focused squads, each owning a key part of the experimentation lifecycle. These squads work collaboratively across teams to deliver a unified, product-first experimentation platform.
Tooling: Designs and simplifies the user interface and experience for experimentation, ensuring a cohesive journey for engineers, data scientists, and product managers.
Analysis: Builds and maintains the analytical backbone, including results computation, inference systems, and statistical methods, enabling fast and reliable business decisions.
Data Foundations: Ensures the reliability and correctness of experimentation data, bridging data producers and downstream analysis, and addressing key data-related blockers.
Experience Foundations: Manages configuration, allocation, and rollout infrastructure, delivering robust and scalable systems for treatment delivery and experience management.
What we expect
You’ll build, scale, and grow a team of outstanding engineers and data scientists, challenging them to continue to ensure Netflix delivers industry-leading capabilities.
You’ll build strong relationships with Data Scientists and Engineers across the business through collaborative partnerships.
You’ll bring a strong execution focus, effectively prioritizing roadmaps in alignment with the overall business needs, and delivering to our partners what we commit to.
You’ll act as an ambassador for experimentation across the company broadly. As a Netflix-wide platform, you’ll constantly seek to onboard new experimentation areas and push the boundaries of where experimentation can go.
You’ve done it before. Experience scaling an experimentation platform is essential. Domain experience in experimentation and causal inference is required.
Our unique culture permeates our way of work - hopefully it resonates with you as much as it does with us. Curious to learn more about our experimentation culture at Netflix? Read up on experimentation culture at Netflix and browse the Netflix Research page.
Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $436,000.00 - $791,000.00. This compensation range will vary based on location.
Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.
Netflix is a unique culture and environment. Learn more here.
Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Job is open for no less than 7 days and will be removed when the position is filled.
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About Netflix

Netflix
PublicAn online streaming platform that enables users to watch TV shows and movies.
10,001+
Employees
Los Gatos
Headquarters
$280B
Valuation
Reviews
4.2
15 reviews
Work Life Balance
4.2
Compensation
4.5
Culture
3.2
Career
3.8
Management
3.0
65%
Recommend to a Friend
Pros
Very high compensation packages (430k-700k)
Fully remote work opportunities
All cash compensation structure
Cons
Lower compensation than expected in some cases
Difficult interview process
Simple/uninteresting technical problems
Salary Ranges
1,869 data points
Mid/L4
Mid/L4 · Analytics Engineer
7 reports
$274,996
total / year
Base
$211,536
Stock
-
Bonus
-
$274,996
$358,605
Interview Experience
4 interviews
Difficulty
4.0
/ 5
Offer Rate
25%
Experience
Positive 25%
Neutral 25%
Negative 50%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
System Design Interview
5
Behavioral Interview
6
Team Matching
7
Final Round
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
News & Buzz
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