Principal Machine Learning Engineer

Zscaler•San Jose, CA

16h•Hybrid

About The Position

About Zscaler Zscaler accelerates digital transformation so our customers can be more agile, efficient, resilient, and secure. Our cloud native Zero Trust Exchange platform protects thousands of 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 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 make a positive difference on a global scale, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity. Our Engineering team built the world’s largest cloud security platform from the ground up, and we keep building. With more than 100 patents and big plans for enhancing services and increasing our global footprint, the team has made us and our multitenant architecture today's cloud security leader, with more than 65 million users in 185 countries. Bring your vision and passion to our team of cloud architects, software engineers, security experts, and more who are enabling organizations worldwide to harness speed and agility with a cloud-first strategy. We're hiring a talented Principal Machine Learning Engineer to join our growing ML/AI team at Zscaler. The team focuses on various cybersecurity use cases including agentic frameworks, threat detection, policy recommendation, content classification, and anomaly detection. In this role, you'll have the opportunity to work on innovative ML/AI projects that address important cybersecurity challenges. This is a hybrid work environment, going into our San Jose, CA office 3 days a week.

Requirements

10+ years of experience as a Machine Learning Engineer or Scientist, with a proven track record of delivering successful projects, along with a solid understanding of machine learning concepts and their applications in cybersecurity
Excellent communication skills with ability to translate complex technical concepts to stakeholders, peers. Record of peer reviewed communication is a plus
Strong proficiency in Algorithms, Game Theory and Optimization, Verification, ML libraries and frameworks
Extensive experience in data modeling, feature engineering, model development, and error analysis
Bachelor's degree in Computer Science, or a related technical field (Master's Degree or PhD preferred)

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 (e.g. AWS, GCP) for AI workloads
Strong experience with agent architectures and SOTA AI frameworks, along with contributions to open-source ML projects, top-tier research publications

Responsibilities

Leading the design and development of cutting edge, production ready AI/ML systems and pipelines, cybersecurity applications and providing technical guidance to junior and mid-level engineers
Optimizing existing machine learning pipelines for improved efficiency and scalability
Exploring and experimenting with advanced AI techniques and architectures to solve complex cybersecurity problems as well as staying updated on the latest advancements in AI and applying them to our cybersecurity solutions
Collaborating with cross-functional teams to define project requirements and ensure alignment with business objectives
Ensuring systems and applications meet reliability, scalability and performance requirements