Senior Staff ML Engineer - Production AI for Security

Zscaler, Inc.; Santa Clara (CA); Hybrid; USD 158,000 - 225,000; Full time

Benefits offered by this job

Time off plans

Parental leave options

Retirement options

In-office perks

Job summary

Zscaler, Inc. is seeking a Senior Staff Machine Learning Engineer for a remote (USA) role. You will drive the development of high‑fidelity risk detection using AI, ML, and data engineering to automate security analysis, reporting to the Manager AI Platform and Data Science.

You will own the end‑to‑end lifecycle of ML components, collaborating with threat research and data teams, and deploying solutions in a production CI/CD environment across the Zscaler AI Platform.

Qualifications

• Deployment of LLM-powered agents with tool calls and multi-step orchestration
• 8+ years of Python development with production-grade systems, validated inputs and data contracts
• Experience with CI/CD, containerization, logging, metrics, observability, on‑call, and cloud infra (AWS)
• Sr. Staff level ownership and leadership of complex engineering initiatives

Responsibilities

• Translate risk identification methods into agent logic with reliable explanations and recommendations
• Collaborate with threat-research to understand data and patterns
• Define data requirements and work with data engineering for pipelines and enrichments
• Apply data-driven quality methods for threat detection, precision/recall balance, and tuning
• Deploy and monitor solutions in production within CI/CD framework

Skills

LLM-powered agents

Python development

CI/CD & observability

Data engineering collaboration

Tools

LangGraph

LangChain

OpenSearch/Elasticsearch

Athena/Presto

Job description

Zscaler, Inc. is seeking a Senior Staff Machine Learning Engineer for a remote (USA) role. You will drive the development of high‑fidelity risk detection using AI, ML, and data engineering to automate security analysis, reporting to the Manager AI Platform and Data Science.

You will own the end‑to‑end lifecycle of ML components, collaborating with threat research and data teams, and deploying solutions in a production CI/CD environment across the Zscaler AI Platform.