Sr. Staff Machine Learning Engineer

Zscaler•San Jose, CA

8h•Hybrid

About The Position

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. We are looking for a Sr. Staff Software Engineer to join our Zscaler Digital Experience (Core Intelligence and Data) team. This is a hybrid role based in San Jose, CA 3 days a week, reporting to the Sr. Manager, Software Engineering. 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.

Requirements

BS in Computer Science with 8+ 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
Hand-on experience with AI modeling, including feature generation, prompt engineering, evaluations and productionization
Experience in the full lifecycle of ML models, including building, deployment, monitoring, and optimization
Expertise in designing and operating distributed microservices using tools like Kubernetes and Docker, and writing production-grade code in Python, Go, or Java

Nice To Haves

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 abnormally detection, event correlation and incident investigation
Proven ability to design and implement high-performance, resilient systems with well-defined service-level objectives

Responsibilities

Own agentic trouble shooting 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