Staff Machine Learning Engineer (Agentic AI)

Zscaler runs one of the world's largest cloud security platforms, and this Staff Machine Learning Engineer seat is on its Exposure Management and Security Operations team. The job is production Gen AI and ML systems, not notebooks: you design and deploy scalable, reliable ML from data ingestion through monitoring, build and maintain MLOps (logging, monitoring, CI/CD for distributed ML), and prototype and champion new AI frameworks into full implementation. There is a mentoring element, guiding junior engineers on system design, but it is an individual contributor Staff role, not people management. It is a hybrid position based in Bangalore. This suits a machine learning engineer with real production and MLOps depth who wants to build AI into a security platform serving over 15 million users, and who is comfortable building the path as they walk it.

What the posting asks for:
- At least 5 years as a Machine Learning Engineer, with proven experience taking ML systems to production.
- Strength across the full lifecycle: data ingestion, model development, deployment and monitoring.
- Solid MLOps practice: logging, monitoring and CI/CD pipelines for distributed ML systems.
- Comfort researching and rapidly prototyping emerging AI and ML frameworks, then driving full scale implementation.

The day to day: you design and deploy production grade Gen AI and ML systems, implement and maintain MLOps, evaluate and prototype new frameworks, mentor junior engineers on system design, and translate business needs into technical solutions with cross functional teams.

Location and ways of working: hybrid, based in Bangalore, reporting to the Sr. Manager, Engineering Strategy, Planning and Analytics.

Honest read: a hands on Staff ML engineering role inside a security business, strong for someone who likes owning production ML and MLOps end to end. It is hybrid Bangalore, not remote, so factor in office days. Mentoring is expected but it is an individual contributor seat.