Job Description

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 designing scalable systems for feature computation and sharing across various ML domains, while collaborating with domain experts to ensure high-quality features and labels for ML models.

Requirements

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

Responsibilities

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

Benefits

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.