Principal Machine Learning Platform Engineer (Prisma AIRS)
Palo Alto NetworksHighlight
Summary
About the Role
About You
- BS/MS or Ph.D. in Computer Science or a related technical field.
- Extensive professional experience in software engineering with a focus on MLOps and productionizing machine learning models.
- Expert-level programming skills in Python.
- Deep experience designing and building large-scale distributed systems on cloud platforms (GCP, AWS, Azure, or OCI).
- Proven track record of leading architecture of complex ML systems and MLOps pipelines using Kubernetes and Docker.
- Mastery of ML frameworks (TensorFlow, PyTorch) and experience with inference optimization tools (ONNX, TensorRT).
- Demonstrated expertise with modern LLM inference engines.
- Experience in a systems language like Go, Java, or C++.
- Strong understanding of popular model architectures (e.g., Transformers, CNNs, GNNs).
- Experience with low-level performance optimization, such as custom CUDA kernel development.
- Experience with data infrastructure technologies (e.g., Kafka, Spark, Flink).
- Familiarity with CI/CD pipelines and automation tools (e.g., Jenkins, GitLab CI, Tekton).
Benefits
- Competitive salary range of $157k–$254k per year.
- Potential for restricted stock units and bonuses.
- Comprehensive employee benefits package.
Palo Alto Networks, the global cybersecurity leader, is shaping the cloud-centric future with technology that is transforming the way people and organizations operate. Our mission is to be the cybersecurity partner of choice, protecting our digital way of life. We help address the world's greatest security challenges with continuous innovation that seizes the latest breakthroughs in artificial intelligence, analytics, automation, and orchestration. By delivering an integrated platform and empowering a growing ecosystem of partners, we are at the forefront of protecting tens of thousands of organizations across clouds, networks, and mobile devices. Our vision is a world where each day is safer and more secure than the one before. For more information, visit www.paloaltonetworks.com.