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# Machine Learning Engineer L4, Algorithms Engineering

- **Company:** Netflix, Inc.
- **Location:** Los Gatos, CA, United States
- **Salary:** $100,000
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), A/B Testing, Big Data, C Sharp (Programming Language), C++ (Programming Language), Apache Hadoop, Apache Hive, Python (Programming Language), Machine Learning, Open Source Technology, Tensorflow, Scala (Programming Language), Software Construction, Software Engineering, Reinforcement Learning, Enterprise Software Applications, Pytorch, Apache Spark, Deep Learning, Keras, Information Technology, Apache Flink, Multiaccess Edge Computing, Software Library
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_9894e338746abc92f551d1512ece3651

## About the Role

To be successful in this role, you need a strong machine learning and software engineering background and have proven experience with large-scale applications involving machine learning. You will need to exhibit strong communication and leadership skills, an ability to set priorities, and an execution focus in a dynamic environment., * A burning desire to solve real-world problems at scale by applying Machine Learning

 * PhD or Masters in Computer Science, Statistics, or any of the related fields
 * Experience with large-scale, real-world machine-learning applications
 * Experience in machine learning, causal inference, reinforcement learning, and econometrics
 * Strong mathematical skills with knowledge of statistical methods
 * Excellent software engineering skills in languages such as Scala, Java, Python, C++ or C#
 * Experience with machine learning libraries TensorFlow, PyTorch, JAX, or Keras
 * Experience with large-scale data frameworks such as Spark, Flink, Hive, or Hadoop
 * Solid understanding of various software engineering best practices and their appropriate application
 * Exceptional problem-solving skills
 * Great interpersonal skills
 * Strong written and verbal communication skills

Preferred, but not required:

 * Experience working with cross-functional teams
 * Experience using Deep Learning, Bandits, CausalML, Reward models, or Reinforcement Learning in real-world applications
 * Experience in applied research in industrial settings
 * Open source contributions
 * Research publications at peer-reviewed journals and conferences on relevant topics
 * Experience scaling and optimizing the training and serving of machine learning models

## Description

We are looking for a passionate and talented machine learning engineer to join our applied ML research team on estimating long-term member satisfaction. As Netflix continues to grow, we are venturing into exciting new frontiers of personalization to help our members find the content they'll most enjoy. To do this, we have to understand which titles, and what experiences in the product, produce the most joy for each member.

In this role, you will contribute to building, implementing, and scaling the next generation of personalization algorithms using techniques such as causal inference, machine learning, reinforcement learning, and econometrics. You will work with a team of experts in these techniques to understand how members experience titles, and how that changes their long-term assessment of their satisfaction with the Netflix service. You will be responsible for operating, as well as innovating, these algorithms in production. You will conduct applied research by conceptualizing, designing, implementing, and validating potential algorithmic improvements. This includes researching and applying cutting-edge machine learning algorithms, running offline experiments, and building online A/B tests to run in production systems. You will partner with people from many disciplines, including behavioral scientists, machine learning researchers, and application engineers.