Senior Machine Learning Engineer

Zscaler · Remote - USA; Santa Clara, California, USA

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 160+ public exchanges globally and thousands of private exchanges 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. 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. What you’ll do (Role Expectations) 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 Who You Are (Success Profile) You thrive in ambiguity and are comfortable building the path as you walk it, viewing unstructured dynamic environments as raw material to create meaningful solutions. You act like an owner with a deep passion for the mission, navigating seamlessly between high-level strategy and hands-on execution to drive outcomes with integrity. You possess a true growth mindset, continuously developing your skills and actively seeking feedback to become a stronger partner and impact-driven teammate. You serve as a positive force, approaching complex technical challenges with contagious constructive energy that inspires your team to stay solution-focused. You are relentlessly data-driven, leveraging analytics and empirical evidence over assumptions to measure what matters and guide informed decisions. What We’re Looking for (Minimum 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 What Will Make You Stand Out (Preferred Qualifications) 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 #LI-KM9 #LI-Remote Zscale

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