About the job
About Zscaler
Zscaler stands as a trailblazer and global authority in zero trust security. Renowned enterprises, critical infrastructure entities, and government bodies rely on Zscaler to safeguard users, branches, applications, data, and devices while propelling digital transformation efforts. With a presence in over 160 data centers worldwide, the Zscaler Zero Trust Exchange platform, bolstered by cutting-edge AI, addresses billions of cyber threats and policy violations daily, enhancing productivity for modern businesses by minimizing costs and complexities.
At Zscaler, the impact of your role supersedes titles, and trust is cultivated through results. We embrace transparency and prioritize constructive, honest discussions, our goal is to swiftly arrive at the best ideas. Our high-performing teams are designed to create significant impact quickly and with utmost quality. We are nurturing a culture of execution centered on customer obsession, collaboration, ownership, and accountability.
We advocate for an “AI Forward, People First” philosophy to foster acceleration and innovation, empowering our workforce to realize their full potential. If you are motivated by purpose, excel in tackling complex challenges, and aspire to make a positive global impact, we encourage you to join Zscaler in shaping the future of cybersecurity.
Role
We are seeking a Principal Machine Learning Engineer to be a vital part of our ML/AI team. This hybrid position is based in San Jose, CA, reporting directly to the VP of AI and ML within the Engineering department.
You will spearhead innovation within our expanding ML/AI team, concentrating on pivotal cybersecurity use cases, including agentic frameworks, threat detection, and anomaly detection. Your contributions will empower organizations globally to leverage speed and agility through a cloud-first strategy while addressing intricate security challenges at scale.
What you’ll do (Role Expectations)
Lead the design and development of state-of-the-art, production-ready AI/ML systems and pipelines, cybersecurity applications, and provide technical mentorship to junior and mid-level engineers.
Enhance existing machine learning pipelines for improved efficiency and performance.
