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.

The Open Connect organization is a critical group within Netflix that builds and manages a global Content Delivery Network that delivers all of Netflix’s streaming video, including Live content, Cloud Gaming, and Advertising. The Open Connect Control Plane team is seeking talented Distributed Systems Software Engineers to craft scalable, reliable, and cost-efficient systems, informed by analytics, needed to build and scale all our offerings, ensuring the best possible Quality-of-Experience for our members globally.

We are committed to building a diverse and inclusive team that brings new perspectives as we solve the next set of challenges at internet scale. 

Engineers on our teams apply their software engineering and analytical problem-solving skills to build a robust, scalable, and highly available distributed infrastructure. This involves answering complex questions and building core systems, such as:

• Building high-scale and resilient services: Cloud services that customers directly hit when they press ‘Play’, as well as algorithms for steering customers to Open Connect appliances for optimal Quality-of-Experience, considering network topology, resource availability, and system load.

  
  
  

• Operational Excellence: Building the necessary tools, visibility, and alerting mechanisms to effectively diagnose, operate, and maintain complex, business-critical systems in real-time.

  
  
  

• Data Analysis: Large-scale distributed software systems and data pipelines for organizing, analyzing, and moving data within large data lakes.

  
  
  

We spend our time trying to answer questions like these:

• How do we design models and systems to adapt appropriately to heterogeneous resource availability, and changing demand, including in real-time?

  
  
  

• How do we build scalable solutions that automate deploying content to servers in our CDN globally as fast as possible, while not impacting performance metrics?

  
  
  

• What algorithms or models do we need to build to understand and optimize hardware utilization, cost efficiency, and resource availability, adapting appropriately to demand, including in real-time?

  
  
  

• How do we make our optimization approaches easy to operate and understand?

  
  
  

• What’s the best way to share system capacity between on-demand Live and pre-positioned VOD content traffic?

  
  
  

• How do we make our systems easy to operate?

  
  
  

• How do we design our systems to react to failure, traffic shifts, and other changes in real-time?

  
  
  

We are looking for someone who identifies with the following: 

• You build robust, responsive, and scalable distributed systems.

  
  
  

• You are comfortable with ambiguity.

  
  
  

• You can iterate quickly on ideas and incorporate feedback.

  
  
  

• You care about building quality software that your teammates can support. 

  
  
  

• You use a data-driven approach when helpful to inform your design decisions.

  
  
  

• You have a passion for operational excellence.

  
  
  

• You believe that fostering an inclusive environment helps everyone do their best work.

  
  
  

Required Qualifications:

• 5+ years of software development with strong experience in Java.

  
  
  

• Experience building and operating business-critical, real-time systems at scale.

  
  
  

• Distributed Systems experience (e.g., building stateful & stateless systems, experience with Casandra, Kafka, etc).

  
  
  

• Experience querying, analyzing, and presenting data from large-scale data lakes (e.g., experience with Python, SQL, Notebooks, Spark SQL).

  
  
  

Preferred Qualifications:

• Basic background in networking and ISP interconnection concepts.

  
  
  

• Experience with Live streaming.

  
  
  

• Experience with ML, optimization algorithms, or behavioral modeling (e.g., experience with PyTorch, Tensorflow, etc.)

  
  
  

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 $388,000.00 - $619,000.00. 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.

Inclusionis 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.