Software Engineer 6 - Feature Infrastructure
About The Position
Netflix is hiring a Software Engineer 6 for its Feature Infrastructure work, building scalable machine-learning data and feature infrastructure. The role focuses on a next-generation ML data and feature platform that helps ML practitioners define and test features and labels while the platform handles computation, storage, and serving for high-throughput training and low-latency inference. It also involves developing a centralized feature and embedding store that allows datasets to be shared across ML domains, including recommendations, payments, games, and ads. The engineer will collaborate with ML practitioners, domain experts, and the broader AI Platform organization to improve the quality of models and the productivity of ML practitioners.
Requirements
- Experience building ML or data infrastructure.
- Strong empathy for and passion about providing a fantastic user experience to ML practitioners.
- Experience building and operating 24/7 high-traffic, low-latency online applications.
- Experience with large-scale data processing frameworks such as Spark, Flink, and Kafka.
- Experience with data storage and serving technologies such as Iceberg and Cassandra.
- Experience working with and optimizing Java and/or Python codebases.
- Experience with public clouds, especially AWS.
- Self-driven and highly motivated team player.
Nice To Haves
- Experience building and operating ML feature stores, such as Chronon.
- Experience building embedding-based retrieval systems.
- Experience working with notebooks such as Jupyter or Polynote.
Responsibilities
- Design and build a near-real-time feature computation engine for high-throughput training and low-latency inference.
- Operate and manage feature computation pipelines and feature-serving infrastructure across multiple ML domains.
- Build and scale systems for performant data loading, transformation, and writing to accelerate training.
- Create frameworks that streamline and expedite the availability of new data for training and serving.
- Develop feature stores that support feature discovery and sharing.
- Make it easier for ML practitioners to define and access features and labels for experimentation and productization.
- Collaborate with ML practitioners, domain experts, and the AI Platform organization to deliver high-quality features and labels and a cohesive end-user experience.
Benefits
- Health plans
- Mental health support
- 401(k) retirement plan with employer match
- Stock option program
- Disability programs
- Health savings and flexible spending accounts
- Family-forming benefits
- Life and serious injury benefits
- Paid leave of absence programs
- Full-time hourly employees accrue 35 days annually for vacation, holidays, and sick paid time off.
- Full-time salaried employees are immediately entitled to flexible time off.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
