About the job
About Zscaler
Zscaler stands as a trailblazer and a global authority in zero trust security. Major corporations, critical infrastructure entities, and government agencies worldwide rely on Zscaler to safeguard users, branches, applications, data, and devices, all while expediting digital transformation efforts. Our expansive network, featuring over 160 data centers globally, leverages the Zscaler Zero Trust Exchange platform alongside advanced AI to thwart billions of cyber threats and policy breaches daily, thus maximizing productivity for modern enterprises by minimizing costs and complexities.
At Zscaler, the impact you make in your role supersedes titles. We cultivate an environment where trust is established through results and prioritize transparency alongside constructive, honest discussions. Our focus is on rapidly arriving at the best ideas. We develop high-performing teams capable of making swift and quality impacts. Our culture promotes a strong execution focus rooted in customer obsession, collaboration, ownership, and accountability.
We advocate for an “AI Forward, People First” philosophy to drive innovation and empower our employees to realize their full potential. If you are motivated by purpose, enjoy tackling complex challenges, and aspire to make a meaningful global impact, we welcome you to bring your expertise to Zscaler and help shape the future of cybersecurity.
Role
We are eager to welcome a Senior Machine Learning Engineer to our Exposure Management & Security Operations team. This hybrid position is based in Bangalore and reports directly to the Sr. Manager of Engineering Strategy, Planning & Analytics. You will become part of the team that constructed the world’s largest cloud security platform from the ground up, helping to scale a multitenant architecture that currently serves over 15 million users globally. Your vision and enthusiasm will be pivotal as we continue to innovate and empower organizations to exploit the speed and agility of a cloud-first strategy.
What You’ll Do (Role Expectations)
- Design and deploy scalable, reliable, and efficient production-grade Gen AI/ML systems, overseeing everything from data ingestion to performance monitoring.
- Drive innovation by researching and assessing emerging AI/ML frameworks, rapidly prototyping new solutions, and advocating for their full-scale implementation.
- Implement and uphold robust MLOps practices, including logging, monitoring, and CI/CD pipelines for distributed ML systems.
- Lead and mentor junior engineers in best practices for system design, fostering technical excellence throughout the team.
- Collaborate...

