Principal Machine Learning Engineer

Overview

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.

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

Minimum Qualifications

• 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)

Preferred Qualifications

• Proven track record of designing, building and shipping end‑to‑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

Salary

Base Pay Range: $182,000 - $260,000 USD1

1 The base salary range listed for this full‑time position excludes commission/bonus/equity (if applicable) + benefits.

Benefits

• Various health plans

• Time off plans for vacation and sick time

• Parental leave options

• Retirement options

• Education reimbursement

• In‑office perks, and more!

Learn more about Zscaler’s Future of Work strategy, hybrid working model, and benefits here.

Legal and EEO Statements

By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines.

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