Staff Machine Learning Engineer (Agentic AI/Gen AI)

Overview

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 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.

Responsibilities

As a Staff Machine Learning Engineer, you will influence technical direction, bridge research and production, and drive technical excellence. You'll lead complex projects, mentor engineers, and build scalable models and systems. Reporting to the Manager of Machine Learning Engineering, your responsibilities will include:

• Designing and deploying scalable, reliable, and efficient production-grade Gen AI/ML systems from data ingestion to monitoring
• Driving the innovation by researching and evaluating emerging AI/ML frameworks, rapidly prototyping novel solutions to validate their feasibility and championing full-scale implementation
• Implementing and maintaining robust MLOps practices, including logging, monitoring, and CI/CD pipelines for distributed ML systems
• Leading and mentoring junior engineers in system design best practices and promoting technical excellence
• Collaborating with cross-functional teams to translate business needs into technical solutions
  
  
  

• 5+ years of experience as an MLE, with a track record of shipping complex, scalable ML systems to production
• Proven experience building Gen AI/ML systems with LLMs, fine-tuning them, using Retrieval-Augmented Generation (RAG) and Agentic AI, and deploying in production
• Proven experience designing and implementing distributed ML systems with deep knowledge of MLOps (monitoring, logging, ops)
• Strong CS foundation (data structures, algorithms, system design) with expertise in Python (scikit-learn, PyTorch/TensorFlow) and SQL for feature engineering, model evaluation, and error analysis
• Excellent communication and interpersonal skills
  
  
  

• Expertise with cloud services (AWS, GCP, Azure) and ML platforms (Kubeflow, SageMaker)
• Proficiency in systems programming languages like Go or Rust, with a deep understanding of distributed systems, OS, and networking fundamentals
• A record of research, publications, or patents in AI/ML
  
  
  

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.

Benefits

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.