Sr Staff ML Engineer (Internet Security))

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 Job Summary You will build machine learning models and develop big data and distributed systems that use the models to analyze and categorize an enormous amount of URLs. You will be a key person in transforming ideas into products which are part of the next generation security platform. The Internet Security Research Team is responsible for innovating new security techniques. Key Responsibilities Design, build, and operate production machine learning systems that balance model quality, cost, latency, and reliability in a security-sensitive environment. Own the end-to-end lifecycle of ML and LLM components, from problem formulation and model development to production deployment, monitoring, and iterative improvement. Integrate ML and LLM-based services with backend systems and data pipelines, ensuring scalability, observability, and safe operation in production. Develop and maintain automated training, evaluation, and retraining pipelines, and build data analysis tools to continuously improve model performance as data and threats evolve. Partner closely with Product Managers and domain experts to translate product and security requirements into robust ML solutions with clear success metrics. Collaborate with software engineers and SREs on release planning, deployment strategies, monitoring, and incident response to ensure reliable and predictable production behavior. Qualifications Your Experience Strong problem solver with collaborative team player with clear communication skills, able to work effectively across engineering, product, and SRE teams. Solid foundation in Machine Learning, Deep Learning, and NLP, with hands-on experience using modern architectures such as transformer-based models and representation learning techniques. Practical experience applying Large Language Models (LLMs) to real-world problems, including text understanding, classification, extraction, summarization, or reasoning over large-scale and noisy data. Experience designing, implementing, and operating LLM-powered components in production, including prompt design, model adaptation or fine-tuning, evaluation, and cost/performance optimization. Familiarity with AI agent–based approaches, such as multi-step inference pipelines, tool-augmented LLM workflows, or systems that combine models, heuristics, and external signals to drive reliable decisions. Experience with MLOps / AIOps practices for operating ML and LLM systems in production, including model lifecycle management, monitoring, logging, alerting, retraining workflows, and debugging production issues. Understanding of model quality, robustness, and safety considerations, including evaluation methodologies, failure modes, and guardrails required for production ML systems in security-sensitive environme ... (truncated, view full listing at source)