Zscaler is seeking a Senior Staff Machine Learning Engineer to join the AI Platform and Data Science team. This is a remote, United States-based role (based in Santa Clara, California) reporting to the Manager of AI Platform and Data Science. The team’s mission is high-fidelity risk identification in customer data, applying AI, machine learning, and data engineering to build data-driven components that automate security analysis. Responsibilities include translating risk identification methods into agent logic and ensuring quality across risk analysis, explanations, and recommendations; collaborating with threat research to understand data and threats and to develop security heuristics; defining data requirements and partnering with data engineering to build pipelines, enrichments, and aggregations; applying a data-driven approach to threat detection, including backtesting, balancing precision versus recall, tuning, and quality control; and deploying and monitoring solutions in production within our CI/CD framework. Requirements include 8+ years of professional Python development with production-grade systems experience and strong SQL/data analytics skills (e.g., pandas, Polars, NumPy); experience building LLM-powered agents in production with tool and function calling, prompt and context engineering, multi-step orchestration (LangGraph, LangChain, or equivalent), and evaluation against ground truth; demonstrated ownership of production reliability (CI/CD, containerization, structured logging and metrics, observability, on-call participation, incident debugging, and AWS inf

Zscaler is seeking a Senior Staff Machine Learning Engineer to join the AI Platform and Data Science team. This is a remote, United States-based role (based in Santa Clara, California) reporting to the Manager of AI Platform and Data Science. The team’s mission is high-fidelity risk identification in customer data, applying AI, machine learning, and data engineering to build data-driven components that automate security analysis. Responsibilities include translating risk identification methods into agent logic and ensuring quality across risk analysis, explanations, and recommendations; collaborating with threat research to understand data and threats and to develop security heuristics; defining data requirements and partnering with data engineering to build pipelines, enrichments, and aggregations; applying a data-driven approach to threat detection, including backtesting, balancing precision versus recall, tuning, and quality control; and deploying and monitoring solutions in production within our CI/CD framework. Requirements include 8+ years of professional Python development with production-grade systems experience and strong SQL/data analytics skills (e.g., pandas, Polars, NumPy); experience building LLM-powered agents in production with tool and function calling, prompt and context engineering, multi-step orchestration (LangGraph, LangChain, or equivalent), and evaluation against ground truth; demonstrated ownership of production reliability (CI/CD, containerization, structured logging and metrics, observability, on-call participation, incident debugging, and AWS inf