Software Engineer L4/L5 - Data and Feature Infrastructure, Machine Learning Platform at Netflix
Interview Preparation Plan
This role is responsible for building and operating a next-generation ML data and feature platform at Netflix to significantly improve the productivity of ML practitioners. The platform will enable ML practitioners to easily define and test ML features and labels, while handling the computation, storage, and serving of feature values for both high-throughput training and low-latency inference use cases. The role also involves building a centralized feature and embedding store for sharing across various ML domains, fostering innovation in areas like personalized recommendations, payments, games, and ads. The successful candidate will work closely with ML practitioners and domain experts to ensure models are built effectively and will collaborate with the broader Machine Learning Platform organization to deliver a cohesive end-user experience. This position requires a strong background in building and operating scalable, low-latency online applications, experience with large-scale data processing frameworks (Spark, Flink, Kafka), and proficiency in Scala and/or Python. Familiarity with public clouds, especially AWS, is essential. The role emphasizes empathy and passion for providing an excellent user experience to ML practitioners, and requires a self-driven, highly motivated, team-player attitude. The goal is to accelerate ML innovation by providing robust and efficient data and feature infrastructure.
Key Responsibilities
- Design and build a near-real-time feature computation engine for ML models.
- Operate and manage feature computation pipelines and serving infrastructure.
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