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 Staff Machine Learning Engineer to join our Shared Platform Services. Reporting to the Director, Engineering; you'll be responsible for:
- Architecting, building and maintaining robust, large-scale distributed systems to support the entire ML pipeline on the client side, including data collection, feature engineering, model training, model evaluation, model deployment, and real-time serving
- Developing functional specifications, assess task requirements and scheduling, and actively participate in the development, debugging, and support of client-side ML solutions
- Solving complex real-world business problems by working closely with various stakeholders, including data scientists, product management, and product engineering teams
- Developing implement, and optimize C/C++ code for the efficient execution of machine learning models on client side or server side depending on the use case
- Integrating and running various machine learning models on client platforms, ensuring optimal performance and resource utilization
- 8+ years of experience as a Software Engineer including 3+ years of ML platform engineer, with a focus on client-side development.
- Experience in C/C++ programming for high-performance applications
- Good understanding of Windows OS and experience building applications on Windows OS using Visual Studio
- Strong experience with algorithms and programming skills in building out data collection/processing infrastructure, Machine Learning model training, and serving platforms on client devices
- Experience with SLM models and running different ML models on client-side environments
- Strong experience with LLMs, agent architectures and prompt engineering
- Experience with ONNX runtime for optimizing and deploying machine learning models
- Advanced degree or certifications in Machine Learning
#LI-GL2
#LI-Hybrid
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.
