Software Engineer – Data and Feature Infrastructure, AI Platform
About The Position
Netflix is hiring a Software Engineer for its AI Platform, focused on building data and feature infrastructure that supports machine learning across business domains. The role will help develop a next-generation ML data and feature platform that enables practitioners to define and test features and labels while the platform handles computation, storage, and serving for both high-throughput training and low-latency inference. The engineer will also help build a centralized feature and embedding store that supports sharing across ML domains. The role involves collaborating with ML practitioners, domain experts, and the broader AI Platform organization to provide high-quality data and a cohesive end-user experience that improves practitioner productivity.
Requirements
- Experience building ML or data infrastructure.
- Strong empathy and passion for 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 applications.
- Operate and manage feature computation pipelines and feature-serving infrastructure for ML models across multiple 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.
- Improve ML practitioner productivity by making it easy to define and access features and labels for experimentation and productization.
- Collaborate with ML practitioners and domain experts to ensure models are built with high-quality features and labels.
- Work with the broader AI Platform organization to deliver 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 salaried employees are immediately entitled to flexible time off
- Full-time hourly employees accrue 35 days annually for paid time off, usable for vacation, holidays, and sick time
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
