AI/ML Intern

Zscaler•San Jose, CA

19h•$35 - $55•Hybrid

About The Position

Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise, we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our 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 say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. 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 be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity. We’re seeking an exceptional AI/ML Intern – ZPA AI Segmentation to join our Engineering Department. This is a Hybrid role, requiring office presence in San Jose, CA, and reporting to the Sr. Director, Software Development Engineering. The AI/ML Intern – ZPA AI Segmentation will focus on developing, training, and deploying machine learning models to enhance the segmentation and policy enforcement capabilities of the Zscaler Private Access (ZPA) platform. This role involves working with large datasets to build intelligent systems that automate security controls, directly contributing to the scalability and intelligence of our zero trust architecture. You will gain hands-on experience applying cutting-edge AI/ML techniques to critical, real-world cloud security challenges.

Requirements

Actively pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Electrical Engineering, or a related quantitative field.
Strong programming skills in Python, with hands-on experience utilizing key machine learning and data libraries (e.g., scikit-learn, Pandas, NumPy, or TensorFlow/PyTorch).
Solid theoretical understanding of core machine learning concepts, including supervised/unsupervised learning, model evaluation metrics, and data structures/algorithms.
Motivated self-starter with a passion for innovation and technology, particularly in applying advanced analytics to real-world security challenges.

Nice To Haves

Prior coursework or project experience related to network protocols, zero trust architectures, network segmentation, or cybersecurity policy enforcement.
Hands-on experience with advanced deep learning frameworks or specific experience in time-series analysis relevant to network telemetry data.

Responsibilities

ZPA AI Segmentation: Collaborate with ZPA engineering teams to develop intelligent segmentation algorithms leveraging AI/ML to enhance network and application security. Design and implement supervised and unsupervised learning techniques for behavior-based segmentation of assets and users.
Agentic AI Design & Development: Support the research and development of Agentic AI systems capable of autonomous decision-making within secure networks. Explore the integration of AI agents into enterprise solution architectures to automate security workflows and enhance proactive threat management.
Advanced User Profiling: Build user profiling solutions powered by AI/ML to identify user patterns, preferences, and potential risks. Assist in the development of predictive analytics models to anticipate user requirements and offer personalized ZPA solutions.
Programming and Code Development: Develop robust and efficient AI capabilities using Java and Python within the ZPA framework. Write clean, modular, and production-ready code while collaborating with experienced senior engineers.
Collaboration & Mentorship: Work closely with cross-functional teams, including senior engineers, product managers, and research scientists, to translate abstract AI/ML concepts into tangible solutions. Seek mentorship and support to strengthen your technical and professional skills during the internship.