Software Engineer 5 – Model Development and Management, AI Platform

Netflix is hiring a Software Engineer 5 to build the user interface layer for its AI Platform, accelerating model creation, evaluation, experimentation, and deployment. The role involves gathering requirements, designing and implementing products for ML use cases, and engaging with researchers, data scientists, and the broader ML community to improve the platform.

Responsibilities:

• We are seeking an ambitious software engineer to join the Model Development and Management team, that is building the user interface layer for Netflix’s AI Platform in order to accelerate the core loop of model creation, evaluation, experimentation, and deployment
• In this role, you'll help shape the future of ML infrastructure at Netflix, with opportunities to contribute to open-source projects and you’ll develop expertise across the full ML lifecycle while working with cutting-edge technologies
• AI Platform and Model Development and Management team are working with various teams at Netflix
• You’ll gather requirements, design, and implement products that help accelerate model development for different ML use cases
• You’ll have the opportunity to work alongside our applied researchers and data scientists on the cutting edge of machine learning
• You will have a strong customer focus and consistently engage with our ML community to source feedback, identify pain points, and opportunities to evolve our platform

Requirements:

• Experience developing platform solutions - SDKs, developer frameworks, or internal tooling used by ML Researchers, ML Engineers, and Data Scientists, emphasizing a user-first approach and demonstrating strong user empathy
• Excellent software design and development skills in Python along with one of Scala, Java, C++
• Experience working on or alongside modern, large-scale ML services. You understand the full lifecycle from data and features to training, experiment tracking, and production deployment, and can build tooling that makes that lifecycle faster and more reliable
• Familiarity with ML workflow orchestration, experiment tracking, or feature/data infrastructure — ideally with tools like Metaflow, Airflow, Kubeflow, MLflow, or similar
• Broad understanding of core machine learning concepts and their application in large-scale, real-world machine-learning systems
• 5+ years of full time software engineering or machine learning experience with a bachelor's and master's degree; or PhD degree
• Experience building machine learning models or LLMs
• Experience designing or building agentic systems
• Experience working with public clouds, especially AWS
• Significant contributions to open source projects