Research Engineer (L4) - Member Lifecycle and Monetization

One of the world's leading entertainment services with 283 million paid memberships in over 190 countries.
United States
$150,000 - $750,000
Machine Learning
Mid-Level Software Engineer
Remote
5,000+ Employees
2+ years of experience
AI · Entertainment · Consumer

Description For Research Engineer (L4) - Member Lifecycle and Monetization

Netflix, a global entertainment leader with 283 million subscribers, is seeking a Research Engineer for their Member Lifecycle and Monetization Data Science & Engineering team. This role is crucial in driving sustainable growth through data-driven solutions and machine learning applications. The position offers an opportunity to work on greenfield ML projects that can drive millions in revenue impact.

The role combines machine learning expertise with software engineering, focusing on developing and deploying ML models that optimize member revenue and conversion experiences. You'll be working with cutting-edge technology while collaborating with cross-functional teams of ML engineers, scientists, and product managers.

This is an excellent opportunity for someone passionate about applying ML at scale, with the position offering competitive compensation ($150,000 - $750,000) and the flexibility to choose between salary and stock options. The remote work environment and Netflix's strong inclusion values create an ideal setting for innovation and growth.

As a Research Engineer, you'll be responsible for designing ML models, creating scalable solutions, and contributing to infrastructure development. The role requires a blend of technical expertise in languages like Scala, Java, and Python, along with strong communication skills to work effectively across teams.

Netflix's unique culture emphasizes freedom and responsibility, offering a chance to work on impactful projects that shape the future of entertainment technology. The position provides an opportunity to work with large-scale systems while contributing to Netflix's continued growth and innovation in the streaming industry.

Last updated a day ago

Responsibilities For Research Engineer (L4) - Member Lifecycle and Monetization

  • Design, implement and operate high impact machine learning models
  • Partner with cross-functional teams to identify high value applications of machine learning
  • Create scalable, production-ready ML solutions
  • Contribute to ML infrastructure development
  • Apply best practices for availability, scalability, operational excellence, and cost management

Requirements For Research Engineer (L4) - Member Lifecycle and Monetization

Python
Java
Scala
  • A degree in Computer Science or related field
  • 2+ years of full time engineering experience
  • Software design and development skills in Scala, Java, and Python
  • Knowledge of software engineering best practices
  • Exceptional communication skills
  • Understanding of core machine learning concepts
  • Experience with end-to-end machine learning pipelines

Interested in this job?

Jobs Related To Netflix Research Engineer (L4) - Member Lifecycle and Monetization

Software Engineer L4, Machine Learning Platform (Metaflow)

Software Engineer position at Netflix focusing on building and improving the Machine Learning Platform (Metaflow) for personalization systems, requiring Python expertise and ML infrastructure experience.

Machine Learning Engineer

Machine Learning Engineer position at OSARO, developing intelligent robotics systems using deep learning, offering $140K-$180K with comprehensive benefits in San Francisco.

Machine Learning Engineer

Machine Learning Engineer position at Flip.shop focusing on developing AI-driven recommendation systems for social commerce platform

Software Engineer - Generative AI, AGIF | Runtime Services

Software Engineering role at Amazon focusing on Generative AI and large language model inference solutions, offering competitive compensation and the opportunity to work with cutting-edge AI technology.

AI Agent Engineer

AI Agent Engineer position at OneTrack.AI, working on warehouse automation technology in New York