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Salary: USD 157,500 - 225,000 / annual
Zscaler is seeking a Senior Staff Machine Learning Engineer to join the AI Platform and Data Science team. The role focuses on high-fidelity risk identification in customer data, combining threat research with AI, machine learning, and data engineering to build automated security analysis components.
You will translate risk identification methods into agent logic, collaborating closely with threat-research teams to understand data, threats, and security heuristics. Key responsibilities include identifying and solving data requirements for analysis, working with data engineering teams on pipelines and enrichments, and following a data-driven quality approach to threat detection through backtesting, precision/recall balancing, and tuning. You will deploy and monitor solutions in production within the company's CI/CD framework.
This is a remote role (USA-based) reporting to the Manager of AI Platform and Data Science. The team's mission centers on catching all threats while minimizing false positives through intelligent, data-driven automation.
Zscaler (NASDAQ: ZS) is a cloud security leader operating the Zero Trust Exchange platform, which protects thousands of customers from cyberattacks and data loss. The company is building an AI-native enterprise where human potential is amplified by machine intelligence to solve complex security challenges.
REQUIREMENTS:
- 8+ years of professional Python development with demonstrated ability to design and maintain production-quality systems with validated inputs, data contracts, and comprehensive unit and integration tests. Hands-on expertise with SQL and Python data analytics libraries (pandas, Polars, NumPy).
- Experience building LLM-powered agents in production: tool and function calling, prompt and context engineering, multi-step orchestration frameworks (LangGraph, LangChain, or equivalent), and evaluation of non-deterministic output against ground truth.
- Demonstrated ownership of production reliability: CI/CD, containerization, structured logging and metrics, observability and alerting, on-call participation, incident debugging in live distributed systems, and familiarity with cloud and infrastructure-as-code in AWS environments.
- Senior Staff level ownership and leadership of emergent requirements, architecture, and complex engineering projects.
PREFERRED QUALIFICATIONS:
- Experience with production AI or ML systems where cost, latency, and accuracy are competing constraints, including model selection, routing, and regression testing.
- Background in cyber threat research, threat modeling, threat hunting, detection engineering, or data-driven risk analysis (fraud detection, adversary profiling, actuarial risk).
- Data engineering experience building and operating pipelines over large-volume event data using SQL, columnar or search-backed stores (OpenSearch/Elasticsearch, Athena/Presto), schema evolution, backfills, and data quality validation.
