Senior Staff Machine Learning Engineer

About Zscaler

Serving thousands of enterprise customers around the world including 45% of Fortune 500 companies, Zscaler (NASDAQ: ZS) was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. As the operator of the world's largest security cloud, Zscaler accelerates digital transformation so enterprises can be more agile, efficient, resilient, and secure. The pioneering, AI-powered Zscaler Zero Trust Exchange platform, which is found in our SASE and SSE offerings, protects thousands of enterprise customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.

Named a Best Workplace in Technology by Fortune and others, Zscaler fosters an inclusive and supportive culture that is home to some of the brightest minds in the industry. If you thrive in an environment that is fast-paced and collaborative, and you are passionate about building and innovating for the greater good, come make your next move with Zscaler. 

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 15 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 looking for an experienced Sr. Staff Machine Learning Engineer to join our Digital Experience team. This role is critical to shape the next generation of Digital Experience with world class tools to identify the insights, root causes, and also enable the agentic AI functionalities. Reporting to the Senior Manager, Machine Learning Engineering, you'll be responsible for:

• Framing high-impact use cases, design agent workflows (tool use, planning, memory, context), and build the frameworks for all the products
• Evaluating and integrating advances in LLMs/SLMs, retrieval, fine-tuning, and inference optimization to deliver reliable, cost-efficient production features
• Designing, implementing, and operating microservices that are observable, resilient, and performant (APIs, data pipelines, orchestration, caching)
• Working with Product, UX, and customers to turn ambiguous problems into measurable wins—clear SLAs, telemetry, and feedback loops

• BS in Computer Science (or related) with 7+ years, or MS/PhD in Computer Science (or related) with 6+ years of experience in solving real world problems leveraging AI/ML and distributed systems
• Exceptional problem-solving skills driven by first-principles thinking, applying expertise in programming, data structures, algorithms, and machine learning
• Proven experience in the full ML model lifecycle— building, deployment, monitoring, and optimization
• Hands-on with modern GenAI stacks (e.g., LangChain/LangGraph, CrewAI, vector stores, RAG, prompts/memory, evaluators)
• Proven experience designing and operating distributed microservices (Kubernetes/Docker, CI/CD, observability; AWS/GCP/Azure) and writing production-grade code in Python, Go, or Java

• Experience fine-tuning and serving proprietary SLMs/LLMs at scale (latency, cost, safety, evals)
• Prior delivery of agentic systems in production, including context engineering and memory management strategies
• Track record building high-throughput, fault-tolerant systems with clear SLOs

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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 Future of Work strategy, 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.