About the job
About Zscaler
Zscaler stands at the forefront of zero trust security, empowering the world’s largest enterprises, critical infrastructure organizations, and government bodies to protect their users, branches, applications, data, and devices. Our cutting-edge Zscaler Zero Trust Exchange platform, fortified by advanced AI, effectively mitigates billions of cyber threats and policy violations daily, enabling organizations to enhance productivity while minimizing costs and complexity.
At Zscaler, we prioritize impact over titles and cultivate a culture built on trust, transparency, and constructive dialogue. We focus on harnessing the best ideas at speed, fostering high-performing teams that deliver impactful results with exceptional quality. Our core values revolve around customer obsession, collaboration, ownership, and accountability.
We embrace an “AI Forward, People First” philosophy to inspire innovation and empower our team members to reach their fullest potential. If you are motivated by purpose, excel in solving intricate challenges, and aim to make a positive global impact, we invite you to join Zscaler and help shape the future of cybersecurity.
Role
We are in search of an experienced Senior Staff Machine Learning Engineer to become an integral part of our Engineering team. This hybrid position is based in Bangalore and reports to the Manager of Machine Learning Engineering.
In this role, you will guide the technical direction, bridge the divide between research and production, and drive technical excellence throughout the organization. You will lead complex projects, mentor junior engineers, and architect the scalable models and systems that power the world’s leading cloud security platform.
Key Responsibilities
- Design and implement scalable, reliable, and efficient production-grade Gen AI/ML systems, from data ingestion to monitoring.
- Drive innovation by researching and assessing emerging AI/ML frameworks, rapidly prototyping innovative solutions, and advocating for full-scale implementation.
- Establish and uphold robust MLOps practices, including logging, monitoring, and CI/CD pipelines for distributed ML systems.
- Mentor junior engineers in system design best practices while fostering a culture of technical excellence.
- Collaborate with cross-functional teams to translate intricate business requirements into impactful technical solutions.
