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Netflix Machine Learning Engineer L4 Algorithms Engineering United States, California 485730556
23.06.2024
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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.
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.
What we are looking for:
- 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
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 $100,000K - $464,000.
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