Principal Machine Learning Engineer

Zscaler•San Jose, CA

2d•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. Role We are looking for a Principal Machine Learning Engineer to join our ML/AI team. This is a hybrid role based in San Jose, CA, reporting to the VP, AI and ML within the Engineering department. You will drive innovation within our growing ML/AI team, focusing on critical cybersecurity use cases like agentic frameworks, threat detection, and anomaly detection. Your work will enable organizations worldwide to harness speed and agility through a cloud-first strategy while solving complex security challenges at scale.

Requirements

Bachelor's degree in Computer Science, or a related technical field
10+ years of experience as a Machine Learning Engineer or Scientist, with a proven track record of delivering successful projects in cybersecurity
Strong proficiency in Algorithms, Game Theory and Optimization, Verification, and ML libraries and frameworks
Extensive experience in data modeling, feature engineering, model development, and error analysis
Excellent communication skills with the ability to translate complex technical concepts to stakeholders and peers

Nice To Haves

Proven track record of designing, building and shipping end-end applications at scale, with familiarity with multi-agent systems and orchestration frameworks
Deep expertise with cloud infrastructure such as AWS or GCP for AI workloads
Strong experience with agent architectures and SOTA AI frameworks, along with contributions to open-source ML projects or top-tier research publications

Responsibilities

Lead the design and development of cutting edge, production ready AI/ML systems and pipelines, cybersecurity applications and provide technical guidance to junior and mid-level engineers
Optimize existing machine learning pipelines for improved efficiency and scalability
Explore and experiment with advanced AI techniques and architectures to solve complex cybersecurity problems while staying updated on the latest advancements in AI
Collaborate with cross-functional teams to define project requirements and ensure alignment with business objectives
Ensure systems and applications meet reliability, scalability and performance requirements