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.
Role
We are looking for an experienced Staff Machine Learning Engineer to join our Engineering team. This role is based in Hyderabad, reporting to the Senior Director, Engineering. You will be responsible for building and maintaining large-scale distributed systems that power our entire ML pipeline, from data collection to real-time serving. You’ll solve complex real-world business problems by partnering closely with data scientists and product teams to deliver impactful automation and intelligence. You will also help design and build Agentic AI systems—developing and orchestrating specialized agents to automate and scale ZPA segmentation workflows, from signal ingestion and reasoning to policy recommendations and enforcement validation.
What you’ll do (Role Expectations)
- Build and maintain large-scale distributed systems to support the whole pipeline including data collection, feature engineering, model training, model evaluation, model deployment, and real-time serving—including Agentic AI components (agent workflows, orchestration, tool integrations, and real-time agent serving).
- Develop functional specifications, assess task requirements and scheduling, and participate in the development, debug, and support—including designing agent behaviors, evaluation strategies (quality/safety/latency), and rollout/monitoring plans for agent-based systems.
- Solve complex real-world business problems like threat detection and business intelligence by working closely with stakeholders including data scientists, product management, and product engineering teams—including building multi-agent solutions that automate analysis and decisioning (e.g., recommendation, triage, and segmentation/policy workflows).
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)
- 4+ years of experience as a AI-ML Engineer
- Experience with applying machine learning for improving key business metrics, optimized models for accuracy, latency
- Experience with researching newer techniques, and innovating for building ML based solutions
- Experience with algorithms in building out data collection/processing infrastructure, Machine Learning model training, and serving platforms
- Expertise in leveraging and augmenting LLM models for software development
What Will Make You Stand Out (Preferred Qualifications)
- Proven track record of designing, building and shipping end-end applications at scale
- Experience identifying and solving problems in data using machine learning systems
- Familiarity with multi-agent systems, agent architectures, prompt engineering and SOTA AI frameworks