Staff Machine Learning Engineer - Data Lake, Anomaly Detection

About Zscaler

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 Staff Software Engineer to join our team. This is a hybrid, based in San Jose, CA 3 days a week 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)

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  Own agentic troubleshooting framework, framing high-impact use cases, designing workflows and playbooks, and building processes for all products



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  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



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  Work with the world class cloud platform and data lakes for feature exploration and generation



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  Handle volume data with the real time pipeline for data processing and aggregation



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  Design, implement, and operate scalable production systems, specifically focusing on microservices, data pipelines, orchestration, and caching

Who You Are (Success Profile)

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  You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.



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  You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.



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  You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.



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  You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.



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  You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking for (Minimum Qualifications)

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  Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain



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  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



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  Proficiency in programming, data structures, algorithms, and machine learning, with exceptional problem-solving skills driven by first-principles thinking



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  Hand-on experience with AI modeling, including feature generation, prompt engineering, evaluations and productionization



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  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)

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  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



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  Experience fine-tuning and deploying proprietary SLMs/LLMs at scale, with a focus on optimizing latency, cost, safety, and evaluations



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  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-Hybrid

#LI-CM3

Zscaler’s salary ranges are benchmarked and are determined by role and level. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations and could be higher or lower based on a multitude of factors, including job-related skills, experience, and relevant education or training.

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

Base Pay Range

$152,000 - $190,000 USD

At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure.

Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including:

• 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 hybrid working model and benefits here .

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

Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.

Pay Transparency

Zscaler complies with all applicable federal, state, and local pay transparency rules.

Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.