Role: Senior Machine Learning Engineer (Remote, USA) at Zscaler. The AI Platform and Data Science team is responsible for high-fidelity risk identification in customer data. You will develop solutions using data analysis, threat research, AI/ML, and data engineering to build data-driven components that automate security analysis. Responsibilities include translating risk identification methods into agent logic; collaborating with threat research to understand data and threats; identifying data requirements and working with data engineering for pipelines, enrichments, and aggregations; applying a data-driven approach to threat detection (backtesting, balancing precision vs recall, tuning, quality control); deploying and monitoring solutions in production within our CI/CD framework. Qualifications include 3+ years of professional Python development with production-quality systems, SQL, and data analytics libraries; experience delivering production AI/ML systems with reliability, CI/CD, containers, logging, observability, and on-call incident debugging in AWS; senior-level ownership of projects, development, and testing; experience building LLM-powered agents in production (tool and function calling, prompt and context engineering, multi-step orchestration frameworks such as LangGraph or LangChain); and preferred backgrounds such as threat research, data engineering pipelines, and handling cost/latency/accuracy tradeoffs. This role is remote-friendly in the United States with Zscaler's hybrid working model.

Role: Senior Machine Learning Engineer (Remote, USA) at Zscaler. The AI Platform and Data Science team is responsible for high-fidelity risk identification in customer data. You will develop solutions using data analysis, threat research, AI/ML, and data engineering to build data-driven components that automate security analysis. Responsibilities include translating risk identification methods into agent logic; collaborating with threat research to understand data and threats; identifying data requirements and working with data engineering for pipelines, enrichments, and aggregations; applying a data-driven approach to threat detection (backtesting, balancing precision vs recall, tuning, quality control); deploying and monitoring solutions in production within our CI/CD framework. Qualifications include 3+ years of professional Python development with production-quality systems, SQL, and data analytics libraries; experience delivering production AI/ML systems with reliability, CI/CD, containers, logging, observability, and on-call incident debugging in AWS; senior-level ownership of projects, development, and testing; experience building LLM-powered agents in production (tool and function calling, prompt and context engineering, multi-step orchestration frameworks such as LangGraph or LangChain); and preferred backgrounds such as threat research, data engineering pipelines, and handling cost/latency/accuracy tradeoffs. This role is remote-friendly in the United States with Zscaler's hybrid working model.