Sr. Staff ML Engineer

About Zscaler

Serving thousands of enterprise customers around the world including 40% 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 a Sr. Staff Machine Learning (ML) Engineer to join our AI Copilot team. This role will be based in our San Jose, CA office (hybrid, 3 days per week in office). Reporting to the Sr. Manager, you'll be responsible for:

• Developing and implementing use cases for the AI Copilot to be utilized by IT administrators, cybersecurity operations, and vulnerability management teams, focusing on both efficiency and user experience.
• Conducting in-depth research on the latest advancements in GenAI technologies and applying these cutting-edge techniques to build AI Copilot use cases.
• Designing, building, and deploying distributed micro-services, ensuring scalability and robustness.
• Collaborating closely with Product Managers and customers to design high-value use cases that meet business objectives and drive product innovation.

• 8+ years of experience delivering end-to-end AI/ML solutions in production.
• Proficiency with mainstream modeling toolkits, including ML/Deep learning (TensorFlow/Keras, PyTorch, Sklearn, Spacy), Data Science (Pandas, Numpy, Spark), and LLM frameworks (HuggingFace, Langchain, Nvidia Nemo stack).
• Solid experience in scalable and distributed system design, with a track record of implementing systems or frameworks with high throughput, resilience, and modularity.
• Proficient knowledge of full-stack languages and frameworks, such as Python, ReactJS, Java (Framework: FARM Stack, MERN Stack, Spring Stack).
• Familiarity with cloud-native DevOps, including practices and tools like Jenkins, Kubernetes (K8s), Docker, Helm, Istio, and Terraform.

• Experience in training language models (LLM or SLM) for production usage.
• Experience or enthusiasm in cybersecurity or digital transformation.