Staff Software Engineer (ML)
Zscaler • Leader in cloud security, providing services to protect enterprise networks and data.
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 a fast-paced and collaborative environment and 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.
About the Role
We're looking for an experienced Staff Backend Engineer to join our team. This role is based in our San Jose, CA office (hybrid, 3 days a week in-office). Reporting to the VP, you will:
- Integrate & manage distributed ML models and inference services while optimizing performance across hybrid environments.
- Architect & optimize APIs and microservices to enable seamless interaction between cloud-based and on-premise ML models and proxy software.
- Ensure security & compliance by implementing robust authentication, authorization, and encryption mechanisms for sensitive AI and customer data.
- Collaborate with ML engineers, DevOps, and security teams to streamline deployment, monitoring, and updates of system components deployed across multiple cloud environments and customer premises.
- Enhance Observability by building logging, monitoring, and tracing systems to ensure reliability across cloud and on-premise installations.
What We're Looking for (Minimum Qualifications)
- 6+ years of experience as a Backend Engineer or similar role, with a focus on designing, building, and scaling systems using distributed ML model inference.
- Deep understanding of optimizing latency, throughput, and resource utilization for AI workloads in distributed systems.
- Strong knowledge of data structures, algorithms, and software engineering principles.
- Proficiency in Java.
- Familiarity with cloud services (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
What Will Make You Stand Out (Preferred Qualifications)
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Experience with ML workloads.