Principal Engineer (Machine Learning)

Palo Alto Networks•Office - USA - CA - Headquarters, CA

2d•Onsite

About The Position

Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place. Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary We are seeking a highly experienced Sr Principal ML Engineer with a good understanding of machine learning principles and algorithms to join our team and drive the development of our User and Entity Behavior Analysis with AI. In this role, you will combine robust backend engineering expertise with machine learning expertise to build, deploy, and maintain a cutting-edge Behavior Analytics system that enhances user experiences and operational efficiency.

Requirements

4+ years of experience using Python to build complex backend systems, ML experience is preferred.
10+ years of experience in software development
Strong background on machine learning and ML frameworks (e.g., TensorFlow, PyTorch)
Experience with cloud-native service development stack on GCP is a plus
Solid grasp of RESTful API design and micro services architecture.
Skilled in diagnosing and solving complex problems while providing detailed technical analysis
Attention to details and high behavioral standards
Team player with can-do attitude to tackle difficult problems and you inspire your team to do the same
High energy and the ability to work in a fast-paced environment
Excellent collaboration and communication with multiple teams
Fast learner and eager to absorb new emerging technologies
M.S./B.S. degree in Computer Science or equivalent experience

Responsibilities

Architect and implement new ML models and pipeline to support efficient model training, validation, and real-time inference.
Optimize the existing ML models and pipeline
Ensure smooth integration of ML solutions into production systems, focusing on performance, reliability, and scalability.
Build automation tools for continuous integration, delivery, and deployment of backend and ML components.
Work closely with cross-functional teams (product, QA, DevOps, and customer support) to align development efforts with business needs.
Troubleshoot and resolve complex issues that arise within both the backend infrastructure and ML models.
Ensure code quality, security, and data privacy by following industry best practices.
Maintain clear and concise documentation for system architecture, API endpoints, and ML model integration processes.