Staff Machine Learning Engineer

About Zscaler Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise , we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate —we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession , collaboration, ownership, and accountability. We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity. Role   We are looking for an experienced Staff Machine Learning Engineer to join our Engineering team. This role is based in Bangalore, reporting to the Senior Engg. Manager - Data + AI. You will be responsible for designing and developing large scale ML Systems that analyze massive volumes of network data to detect anomalies, threats, and patterns in near real-time. You’ll solve complex real-world business problems by partnering closely with data architects and product teams to deliver impactful automation and intelligence, including the design and orchestration of specialized autonomous agents. What you’ll do (Role Expectations) Build and maintain large-scale distributed systems to support the full ML lifecycle, including data collection, feature engineering, and Agentic AI components like agent workflows and real-time serving Solve complex business problems such as threat detection by collaborating with data architects and product teams to build multi-agent solutions that automate analysis and decisioning Partner with cross-functional teams to assess requirements, manage scheduling, and lead the development and debugging of agent-based systems Support the rollout and monitoring plans for production-grade ML systems to ensure performance, observability, and scalability Who You Are (Success Profile) You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful. You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution. You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact. You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust. You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose. What We’re Looking for (Minimum Qualifications) 5+ years of experience as an AI-ML Engineer with technical proficiency in Java, Springboot, Python, and PyTorch or TensorFlow Proven experience writing high-performance queries for large-scale analytics platforms such as Azure Data Explorer (ADX/Kusto) or Google BigQuery, including partitioning-aware patterns Deep expertise in designing and deploying anomaly detection using tree-based models, statistical techniques, and streaming ML approaches Hands-on experience developing multi-agent orchestration, agent-to-agent communications, and autonomous decision-making workflows Strong technical background with distributed infrastructure and public cloud platforms like Azure, GCP, or AWS What Will Make You Stand Out (Preferred Qualifications) A track record of shipping end-to-end applications at scale that process billions of events Willingness to work across the full spectrum of Big Data and AI-based solutions Hands-on experience with S