Role Overview
Netflix is seeking a highly skilled and experienced Machine Learning Engineer to join the Content & Conversation Modeling team. In this role, you will design, build, and optimize large-scale ML systems that directly influence some of Netflix’s most critical decisions, including which titles to acquire, how to schedule them, and how to strengthen the content catalog to serve members around the globe. You will be working on challenges at the intersection of content engagement prediction, title performance forecasting, catalog optimization, and advertising effectiveness, tackling problems that require both deep technical expertise and innovative thinking.
Key Responsibilities
-
Develop advanced ML models that predict how global audiences engage with Netflix content, both current catalog and future launches, supporting decision-making across multiple business domains.
-
Design, implement, and deploy scalable ML systems capable of handling Netflix’s massive data scale, ensuring reliability, efficiency, and flexibility for future growth.
-
Automate ML pipelines and workflows covering data preparation, model training, hyperparameter tuning, and deployment, enabling faster research-to-production transitions and repeatable experimentation.
-
Optimize inference performance and system efficiency, ensuring models are production-ready for high-throughput, distributed environments across the Netflix ecosystem.
-
Improve monitoring, observability, and debugging tools to guarantee ML systems remain accurate, trustworthy, and resilient once deployed at scale.
-
Collaborate closely with scientists, engineers, and product teams, ensuring alignment of research prototypes with product goals and smooth integration into downstream applications.
-
Translate research into robust production systems, enhancing maintainability, scalability, and performance while preserving cutting-edge capabilities.
-
Evaluate and adopt emerging ML infrastructure technologies, identifying opportunities to improve efficiency, scalability, and development velocity.
Qualifications
-
5+ years of industry experience in designing, developing, and deploying ML systems at scale, preferably within distributed environments and high-volume data settings.
-
Advanced degree (MS or PhD) in Computer Science, Electrical Engineering, or a related technical discipline with a concentration in ML/AI.
-
Strong foundation in machine learning algorithms and techniques, including supervised learning, unsupervised learning, and deep learning architectures used for recommendation systems, forecasting, or content engagement models.
-
Demonstrated success in deploying ML models at scale, with hands-on experience in monitoring, evaluating, and maintaining models in production.
-
Expertise in feature engineering, large-scale data pipelines, and model lifecycle management for complex, high-dimensional data; familiarity with Spark or similar frameworks is essential.
-
Proficiency in Python and deep knowledge of ML/DL frameworks such as PyTorch, Jax, or MetaFlow, with the ability to write high-quality, production-level code.
-
Proven ability to solve complex problems with innovative solutions, adapting methods from academic research and industry literature to real-world business challenges.
-
Excellent communication skills, with the ability to clearly explain complex technical details to both technical audiences and non-technical stakeholders, ensuring strong collaboration across teams.
-
Commitment to Netflix’s cultural values, with a mindset that brings new perspectives, diversity of thought, and continuous improvement to the team and broader organization.