Senior Machine Learning Engineer

📋 Job Overview

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform.

We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler.

🏢 About Zscaler

At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure.

🎯 The Role

We are looking for a Senior Machine Learning Engineer to join our team. This is a remote (USA) role, reporting to the Manager AI Platform and Data Science in the AI Platform and Data Science department. This team’s mission is high-fidelity risk identification in customer data. Our goals are to catch all threats while minimizing noise. To do this, you will develop solutions applying data analysis and threat-research, while using AI, machine learning, and data engineering to build quality, data-driven components to automate security analysis.

✅ Key Responsibilities

• Translate risk identification methods into agent logic, understanding the benefits and limitations of agents, and how to ensure quality in different types of tasks, including risk analysis, explanations, and recommendations
• Collaborate closely with threat-research to understand data and threats and their approach to developing security heuristics
• Identify and solve data requirements for analysis, developing and collaborating with data engineering teams for pipelines, enrichments, and aggregations
• Follow a data-driven quality approach to threat-detection: including backtesting, balancing precision vs recall, tuning, and quality control
• Deploy and monitor your solutions in production in our CI/CD framework

📌 Required Qualifications

• 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
• 3+ 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, alongside hands-on expertise with SQL and Python data analytics libraries (e.g., pandas, Polars, NumPy)
• Demonstrated ownership of production reliability: CI/CD, containerization, structured logging and metrics, observability and alerting, on-call participation, and incident debugging in a live distributed system, with familiarity with cloud and infrastructure-as-code in an AWS environment
• Senior-level ownership and leadership of projects, development, and testing

⭐ Desirable Experience

• Experience with production AI or ML systems where cost, latency, and accuracy are competing constraints, including handling model selection, routing, and regression testing
• Background in cyber threat research, threat modeling, threat hunting, detection engineering, or previous experience in data-driven risk analysis, fraud detection, adversary profiling and targeting, actuarial risk, or close collaboration with these types of teams to understand risk analysis and investigation processes
• Data engineering experience, including building and operating pipelines over large-volume event data: SQL, columnar or search-backed stores (OpenSearch/Elasticsearch, Athena/Presto, or similar), plus schema evolution, backfills, and data quality validation

🎁 Benefits

The base salary range listed for this full-time position excludes commission/ bonus/ equity (if applicable) + benefits.

Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including:

• Various health plans
• Time off plans for vacation and sick time
• Parental leave options
• Retirement options
• Education reimbursement
• In-office perks, and more!