Staff Machine Learning Engineer - Data Lake, Anomaly Detection

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Staff Software Engineer to join our team. This is a Hybrid role, reporting to the Sr. Manager, Software Engineering in the Zscaler Digital Experience (Core Intelligence and Data) department. You will join the team responsible for building the world’s largest cloud security platform, helping us enhance services and increase our global footprint. You will play a pivotal role in enabling organizations worldwide to harness speed and agility through a cloud-first strategy, leveraging our multitenant architecture that serves over 15 million users. What you’ll do (Role Expectations) Own agentic troubleshooting framework, framing high-impact use cases, designing workflows and playbooks, and building processes for all products Evaluate and integrate state-of-the-art GenAI advances to deliver reliable and cost-efficient production features, utilizing LLMs, various machine learning models, data processing, fine-tuning, and inference optimization Work with the world class cloud platform and data lakes for feature exploration and generation Handle volume data with the real time pipeline for data processing and aggregation Design, implement, and operate scalable production systems, specifically focusing on microservices, data pipelines, orchestration, and caching Who You Are (Success Profile) Thrive in ambiguity, comfortably building the path as you walk it and viewing dynamic environments as opportunities to construct meaningful solutions. Operate with a strong ownership mindset, combining a passion for the mission with high integrity and the ability to navigate seamlessly between high-level strategy and hands-on execution. Demonstrate a proactive problem-solving focus, eagerly running toward challenges and remaining laser-focused on delivering high-impact outcomes. Build high-trust collaboration, prioritizing team success, welcoming constructive feedback, and practicing clear and respectful candor to establish strong partnerships. Maintain a continuous growth mindset, actively seeking feedback and development to grow as a partner, teammate, and purpose-driven leader. What We’re Looking for (Minimum Qualifications) Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain BS in Computer Science with 6+ years of experience, or MS/PhD with 5+ years of experience solving real-world problems using AI/ML and distributed systems Proficiency in programming, data structures, algorithms, and machine learning, with exceptional problem-solving skills driven by first-principles thinking Hands-on experience with AI modeling, including feature generation, prompt engineering, evaluations, and productionization Experience in the full lifecycle of ML models (building, deployment, monitoring, optimization) alongside expertise in designing and operating distributed microservices using Kubernetes and Docker in Python, Go, or Java What Will Make You Stand Out (Preferred Qualifications) Proven ability to leverage AI technologies and workflows to drive measurable operational efficiency Experience designing and scaling autonomous AI agents, agentic orchestration workflows, and advanced large language model (LLM) tooling to automate complex cloud infrastructure troubleshooting or incident response Experience fine-tuning and deploying proprietary SLMs/LLMs at scale, with a focus on optimizing latency, cost, safety, and evaluations Experience delivering production-ready AI systems, including expertise in anomaly detection, event correlation, incident investigation, and resilient systems with well-defined service-level objectives #LI-CM3 #LI-Hybrid Zscaler’s salary ranges are benchmarked and are determined by role and level. The range displayed on