Security ML Engineer (L5)

Netflix is a leading entertainment company focused on pushing the boundaries of storytelling through innovative technology. The Security ML Engineer will build production ML systems to detect fraud and automate security decisions, collaborating with various teams to enhance security measures across Netflix's global member base.

Responsibilities:

• You will build production ML systems that detect fraud and abuse patterns across Netflix's global member base and device ecosystem
• You will deploy real-time inference systems that provide security signals to authorization and policy engines, while deciding when and where ML is the right solution to security challenges
• You will solve challenges including unlabeled/mislabeled data, highly imbalanced datasets, concept drift, and evasion attacks
• You will design metrics and observability to measure model performance and security impact in production
• You will build scalable solutions to automate security decisions by creating ML-driven policies that balance security, member experience, and business needs
• You achieve your goals by collaborating cross-functionally with security engineers, data scientists, infrastructure teams, and product managers to deliver end-to-end solutions

Requirements:

• 5+ years of industry experience designing, building, and deploying ML systems in production environments, including Production ML expertise with Python or Java, and modern ML frameworks
• Strong ML foundation in supervised and unsupervised learning, anomaly detection, classification, and statistical modeling techniques (e.g., logistic regression, random forests, gradient boosting, isolation forests, autoencoders) and understanding of the trade-offs with each of those models
• Big data proficiency using distributed computing platforms like Spark, along with SQL and data pipeline development
• You are experienced with programming languages such as Python and/or Java in a big data environment
• Security mindset with curiosity about attacker incentives, threat modeling, and adversarial techniques
• Systems thinking for building scalable, low-latency inference systems that handle millions of requests
• You operate effectively across teams and disciplines in highly ambiguous and rapidly changing environments
• A strong communicator & collaborator in varying contexts & environments