\\\\Our Mission\\\\ At Palo Alto Networks® everything starts and ends with our mission: Being the cybersecurity partner of choice, protecting our digital way of life. Our vision is a world where each day is safer and more secure than the one before. We are a company built on the foundation of challenging and disrupting the way things are done, and were looking for innovators who are as committed to shaping the future of cybersecurity as we are. \\\\Who We Are\\\\ We believe collaboration thrives in person. Thats why most of our teams work from the office full time, with flexibility when its needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. \\\\Your Career\\\\ With Prisma AIRS, Palo Alto Networks is building the world's most comprehensive AI security platform. Organizations are increasingly building complex ecosystems of AI models, applications, and agents, creating dynamic new attack surfaces with risks that traditional security approaches cannot address. In response,Prisma AIRS delivers model security, posture management, AI red teaming, and runtime protection. Our customers can confidently deploy AI-driven innovation while ensuring a formidable security posture from development through runtime. As a Senior Principal Machine Learning Engineer, you will drive research on cutting-edge areas, including AI-Native Security (LLM, AI Agent, Model Supply-Chain, Runtime AI) and the broader LLM ecosystem security. You will leverage this research to identify and bring up new product opportunities. You will collaborate closely with engineering teams to deploy models, ensuring maximum product impact. Furthermore, you will foster cross-functional collaboration and serve as an AI thought leader both within the company and in the security/LLM community. Beyond individual contribution, you will lead complex technical projects, mentor senior engineers, and set the standard for performance, scalability, and engineering excellence across the organization. Your decisions will have a profound and lasting impact on our ability to deliver cutting-edge AI security solutions at a massive scale. \\\\Your Impact\\\\ \\+ Lead the architectural design of a highly scalable, low-latency, and resilient ML inference platform capable of serving a diverse range of models for real-time security applications. \\+ Define technical approaches to less-defined product requirements, ensuring the best fit between product features and technical implementation. Explore new product opportunities by maintaining a deep understanding of LLM and Generative AI research trends. \\+ Technical Leadership: Provide technical leadership and mentorship to the team, driving best practices in MLOps, software engineering, and system design. \\+ Strategic Optimization: Drive the strategy for model and system performance, guiding research and implementation of advanced optimization techniques like custom kernels, hardware acceleration, and novel serving frameworks. \\+ Set The Standard: Establish and enforce engineering standards for automated model deployment, robust monitoring, and operational excellence for all production ML systems. \\+ Cross-Functional Vision: Act as a key technical liaison to other principal engineers, architects, and product leaders to shape the future of the Prisma AIRS platform and ensure end-to-end system cohesion. \\+ Solve the Hardest Problems: Tackle the most ambiguous and challenging technical problems in large-scale inference, from mitigating novel security threats to achieving unprecedented performance goals. \\\\Your Experience\\\\ \\+ BS/MS or Ph.D. in Computer Science, a related technical field, or equivalent practical experience. \\+ Extensive professional experience in software engineering with a deep focus on MLOps, ML systems, or productionizing machine learning models at scale. \\+ Expert-level programming skills in Python are required; experience in a systems language like Go, Java, or C++ is nice to have. \\+ Deep, hands-on experience designing and building large-scale distributed systems on a major cloud platform (GCP, AWS, Azure, or OCI). \\+ Proven track record of leading the architecture of complex ML systems and MLOps pipelines using technologies like Kubernetes and Docker. \\+ Mastery of ML frameworks (TensorFlow, PyTorch) and extensive experience with advanced inference optimization tools (ONNX, TensorRT). \\+ A strong understanding of popular model architectures (e.g., Transformers, CNNs, GNNs) is a must. A deeper understanding of attention mechanisms and related knowledge is a plus. \\+ Demonstrated expertise with modern LLM inference engines (e.g., vLLM, SGLang, TensorRT-LLM) is required. Open-source contributions in these areas are a significant plus. \\+ Experience with low-level performance optimization, such as custom CUDA kernel development or using Triton Language, is a plus. \\+ Experience with data infrastructure technologies (e.g., Kafka, Spark, Flink) is great to have. \\+ Familiarity with CI/CD pipelines and automation tools (e.g., Jenkins, GitLab CI, Tekton) is a plus. \\\\The Team\\\\ Our Prisma AIRS team is a group of highly motivated and innovative engineers and researchers dedicated to solving the most challenging problems in AI security. We thrive in a collaborative environment where we value creativity, ownership, and a commitment to excellence. You will have the opportunity to work with cutting-edge technology and make a significant impact on the future of cybersecurity. \\\\Compensation Disclosure\\\\ The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be between $185,200 - $299,450/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here () . \\\\Our Commitment\\\\ Were problem solvers that take risks and challenge cybersecuritys status quo. Its simple: we cant accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at . Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship?: Yes

The role requires extensive professional experience in software engineering with a focus on MLOps, ML systems, or productionizing machine learning models at scale. Expert-level programming skills in Python are mandatory. Experience in designing and building large-scale distributed systems on a major cloud platform such as GCP, AWS, Azure, or OCI is essential. A proven track record of leading the architecture of complex ML systems and MLOps pipelines using technologies like Kubernetes and Docker is necessary. Mastery of ML frameworks like TensorFlow and PyTorch, along with advanced inference optimization tools such as ONNX and TensorRT, is required. A strong understanding of popular model architectures, including Transformers, CNNs, and GNNs, is a must, with expertise in modern LLM inference engines like vLLM, SGLang, and TensorRT-LLM being mandatory. A BS/MS or Ph.D. in Computer Science, a related technical field, or equivalent practical experience is also required.