Principal Machine Learning Engineer

Our Engineering team built the world’s largest cloud security platform from the ground up, and we keep building. With more than 100 patents and big plans for enhancing services and increasing our global footprint, the team has made us and our multitenant architecture today's cloud security leader, with more than 15 million users in 185 countries. Bring your vision and passion to our team of cloud architects, software engineers, security experts, and more who are enabling organizations worldwide to harness speed and agility with a cloud-first strategy. We're hiring a talented Principal Machine Learning Engineer to join our growing ML/AI team at Zscaler. The team focuses on various cybersecurity use cases including threat detection, policy recommendation, malware detection, content classification, and anomaly detection. In this role, you'll have the opportunity to work on innovative ML/AI projects that address important cybersecurity challenges. This is a hybrid work environment, going into our San Jose, CA office 3 days a week. Reporting to the Sr. Director, Machine Learning, you'll be responsible for: Leading the design and development of cutting-edge, production-ready ML systems and pipelines, cybersecurity applications, and providing technical guidance to junior and mid-level engineers. Optimizing existing machine learning pipelines for improved efficiency and scalability. Exploring and experimenting with advanced AI techniques and architectures to solve complex cybersecurity problems as well as staying updated on the latest advancements in AI and applying them to our cybersecurity solutions. Collaborating with cross-functional teams to define project requirements and ensure alignment with business objectives. Ensuring systems and applications meet reliability, scalability, and performance requirements. What We're Looking for (Minimum Qualifications) 10+ years of experience as a Machine Learning Engineer, with a proven track record of delivering successful projects, along with a solid understanding of machine learning concepts and their applications in cybersecurity. Excellent communication skills with the ability to translate complex technical concepts to stakeholders. Strong proficiency in Python, SQL, ML libraries, and frameworks. Extensive experience in data modeling, feature engineering, model development, and error analysis. Bachelor's degree in Computer Science, Engineering, or a related technical field (Master's Degree or PhD preferred). What Will Make You Stand Out (Preferred Qualifications) Proven track record of designing, building, and shipping end-to-end applications at scale, with familiarity with multi-agent systems and orchestration frameworks. Strong experience with LLMs, agent architectures, prompt engineering, and SOTA AI frameworks, along with contributions to open-source ML projects and top-tier research publications. Deep expertise with cloud infrastructure (e.g., AWS, GCP) for AI workloads.

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