2 days ago
Base Salary
$500k - $860k/yr
Responsibilities
- Design and build near-real-time feature computation engines for ML training and inference.
- Operate and manage feature computation pipelines and feature-serving infrastructure across multiple ML domains.
- Build scalable systems for performant data loading, transformation, and writing to accelerate training.
- Create frameworks that improve the availability, discovery, and sharing of data, features, and labels.
- Develop centralized feature and embedding stores.
- Improve ML practitioner productivity by simplifying feature and label definition, experimentation, and productization.
- Collaborate with ML practitioners, domain experts, and the broader AI Platform organization.
Requirements
- Experience building ML or data infrastructure.
- 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 optimizing Java and/or Python codebases.
- Experience with public clouds, especially AWS.
- Strong empathy for and commitment to providing a strong user experience for ML practitioners.
- Preferred: experience operating ML feature stores such as Chronon.
- Preferred: experience building embedding-based retrieval systems.
- Preferred: experience with Jupyter or Polynote notebooks.
- Self-driven, highly motivated team player.
Benefits
- Comprehensive health plans and mental health support.
- 401(k) retirement plan with employer match.
- Stock option program, disability programs, health savings and flexible spending accounts.
- Family-forming benefits and life and serious injury benefits.
- Paid leave programs; full-time salaried employees are immediately entitled to flexible time off.
- Full-time role with a compensation structure consisting of annual salary and stock options, with compensation varying by location.
Tech Stack
Categories
Data EngineeringML Engineering
About Netflix
Netflix builds and operates a global streaming service for TV series, films, games, and live programming, and produces original content through its in-house studio. It serves consumers in 190+ countries via subscription and ad-supported plans on internet-connected devices. Founded in 1997 and headquartered in Los Gatos, California, Netflix is a public company traded on NASDAQ (NFLX).