Netflix is seeking a professional to build a next-generation machine learning data and feature platform aimed at enhancing the productivity of ML practitioners. The role involves creating scalable infrastructure for ML features and labels, enabling innovation across various domains such as personalized recommendations and payments.

• Experience in building ML or data infrastructure
• Strong empathy and passion for providing a fantastic user experience to ML practitioners
• Experience in building and operating 24/7 high-traffic and low-latency online applications
• Experience with large-scale data processing frameworks such as Spark, Flink, and Kafka
• Experience in working with and optimizing Scala and/or Python codebases
• Experience with public clouds, especially AWS
• Self-driven and highly motivated team player

• Design and build a near-real-time feature computation engine to generate ML features for both high-throughput training and low-latency inference applications
• Operate and manage the feature computation pipelines and feature serving infrastructure for various ML models across multiple ML domains
• Build and scale systems that accelerate training through performant data loading, transformation, and writing
• Create frameworks to streamline and expedite the availability of new data for training and serving
• Develop feature stores that enable feature discovery and sharing
• Increase the productivity of ML practitioners by making it easy to define and access features and labels for experimentation and productization

• Employees at Netflix are often offered flexible, people-first benefits—unlimited time away, generous parental leave, global family-forming support, mental-health programs (mindfulness, free counseling/coaching), and health coverage tailored by country. Financially, Netflix pays at personal top-of-market and lets employees choose their mix of cash vs. fully-vested 10-year stock options, alongside donation and volunteer matching. Convenience perks can include trust-based travel/expense policies, relocation support, and “Work, Not Drive” rideshare flexibility.