Software Engineer 6 – Feature Infrastructure

Job not on LinkedIn

🔥 1 minute ago

🇺🇸 United States – Remote

💵 $600k - $1.1M / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 0%

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Netflix

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1997

📱 Media

👥 B2C

Media • B2C

Netflix is a global streaming entertainment company and content producer whose stated mission is "to entertain the world. " It operates a consumer-facing subscription platform offering on-demand TV shows, films, and original programming, and also runs a public careers site emphasizing culture, inclusion, and hiring accommodations. The provided text highlights Netflix’s focus on recruiting talent worldwide, its work-life and culture pages, and its public-facing employer materials.

📋 Description

• Build a next-generation ML data and feature platform to improve ML practitioner productivity • Enable ML practitioners to define and test ML features and labels while the platform handles computation, storage, and serving • Build a centralized feature and embedding store for sharing across ML domains • Collaborate with ML practitioners and domain experts to ensure high-quality features and labels • Work with the broader AI Platform organization to deliver a cohesive end-user experience • Design and build a near-real-time feature computation engine • Operate and manage feature computation pipelines and feature-serving infrastructure • Build and scale systems for performant data loading, transformation, and writing • Create frameworks to expedite new data availability for training and serving • Develop feature stores that enable feature discovery and sharing • Improve the productivity of ML practitioners by simplifying feature and label definition and access

🎯 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 with data storage and serving technologies such as Iceberg and Cassandra • Experience in working with and optimizing Java and/or Python codebases • Experience with public clouds, especially AWS • Self-driven and highly motivated team player • Preferred: Experience in building and operating ML feature stores, such as Chronon • Preferred: Experience in building embedding-based retrieval systems • Preferred: Experience working with Notebooks such as Jupyter or Polynote

🏖️ 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 paid time off to be used for vacation, holidays, and sick paid time off • Full-time salaried employees are immediately entitled to flexible time off