Senior Principal ML Engineer — Behavior Analytics

Palo Alto Networks, Inc.; Santa Clara (CA); On-site; USD 185,000 - 299,000; Full time

Job summary

Palo Alto Networks, Inc. is seeking a Sr Principal ML Engineer to lead the development of a cutting-edge Behavior Analytics system. You will blend robust backend engineering with machine learning to build and deploy scalable models that enhance user experiences and operational efficiency.

You will design ML pipelines, integrate them into production, and work with product, QA, DevOps, and support teams to deliver reliable solutions in a fast-paced environment.

Qualifications

• 4+ years of Python for backend systems; ML experience preferred; 10+ years of software development.
• Strong ML framework experience (TensorFlow, PyTorch).
• Experience with cloud-native service development on GCP is a plus.
• Solid RESTful API design and microservices architecture.

Responsibilities

• Architect and implement ML models and pipelines for training, validation, and real-time inference.
• Optimize existing ML models and pipelines.
• Ensure smooth production integration with performance, reliability, and scalability.
• Build automation tools for CI/CD of backend and ML components.
• Collaborate with cross-functional teams to align development with business needs.
• Troubleshoot and resolve complex backend and ML issues.
• Ensure code quality, security, and data privacy best practices.
• Maintain architecture, API, and ML integration documentation.

Skills

Python backend

ML frameworks (TensorFlow, PyTorch)

RESTful API design

Cloud: GCP

Software development experience

Problem solving

Team collaboration

Fast learning

Education

M.S./B.S. in Computer Science or equivalent

Tools

TensorFlow

PyTorch

GCP Cloud

Job description

Palo Alto Networks, Inc. is seeking a Sr Principal ML Engineer to lead the development of a cutting-edge Behavior Analytics system. You will blend robust backend engineering with machine learning to build and deploy scalable models that enhance user experiences and operational efficiency.

You will design ML pipelines, integrate them into production, and work with product, QA, DevOps, and support teams to deliver reliable solutions in a fast-paced environment.