Full-Stack Engineer 5 – AI Insights & Visualizations, AI Platform

Netflix is a company dedicated to entertaining the world through innovative storytelling and technology. They are seeking a Full-Stack Engineer to develop end-to-end solutions that enhance the productivity and innovation of AI/ML practitioners by building internal tools for visualizing and monitoring AI/ML models.

Responsibilities:

• Develop and maintain web-based internal tools and platforms that help AI/ML practitioners visualize, monitor, and operate AI/ML models and pipelines
• Build and improve dashboards for model observability, anomaly and drift detection, cost monitoring, and system health
• Collaborate with users and stakeholders to gather feedback and deliver intuitive, seamless, and impactful user experiences
• Continuously improve our systems, codebase, and team processes to enhance overall performance
• Introduce and champion best practices in full-stack development
• Partner with engineering, product, and research teams distributed across multiple US-based time zones to deliver impactful solutions and drive ML/AI innovation at Netflix

Requirements:

• Proficiency in modern UI frameworks (React preferred), JavaScript/TypeScript, Node.js, and building scalable backend systems (Java, Scala, or similar; Spring Boot or equivalent frameworks)
• Hands-on experience with public cloud platforms (AWS, Azure, or GCP)
• Familiarity with ML model lifecycle management, logging, metrics, analytics, and building tools for data visualization and observability
• Experience in maintaining and improving legacy systems, with the ability to evaluate tradeoffs between refactoring, rebuilding, and buying solutions
• Excellent written and verbal communication skills, with a proactive approach to cross-functional collaboration
• BS/MS in Computer Science, Applied Math, Engineering, or a related field, or equivalent practical experience
• Experience building UI tools for ML practitioners or data scientists
• Deep understanding of ML model development, deployment, and monitoring workflows
• Track record of shipping and refining products based on user feedback
• Passion for data-driven product development and improving engineering productivity