Machine Learning Engineer

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 As a Machine Learning Engineer on our Internet Security Research Team, you will be a key innovator transforming ideas into products for our next-generation security platform. You will work with data scientists and security researchers to implement projects that detect and defend against emerging web security threats. This role is part of our dedicated 2026 New Hire cohort, with an anticipated start date in August 2026. Key Responsibilities Perform in-depth data analysis to deeply understand security data and the threat domain. Design, train, and evaluate machine learning algorithms to significantly improve the analytical performance of threat detection models. Build and productionize machine learning models and develop the distributed systems that utilize them to analyze and categorize enormous volumes of URLs. Design and build robust, scalable machine learning systems, carefully balancing cost with model performance. Establish automated training pipelines and develop data analytics tools to incrementally enhance model performance on a growing dataset. Proactively collaborate with data scientists, security researchers, and Product Managers to gather requirements, design, and implement systems. Challenge existing approaches curiously and positively to simplify complex systems and improve efficiency. Work effectively with other engineers and SREs on release, deployment, and operational processes, ensuring alignment and accountability. Qualifications Required Qualifications MS or PhD in Machine Learning, Computer Science, Data Science, or a related field, with graduation expected between December 2025 and July 2026. Proficiency in at least one programming language such as Python, Java, or Golang. Experience applying supervised and/or unsupervised machine learning algorithms on various data types. Extensive knowledge of ML frameworks and libraries (e.g., Scikit-learn, MLlib, Tensorflow, Keras, Kubeflow). Experience with big data technologies and infrastructure, such as Hadoop or Spark. Preferred Qualifications Working knowledge of Natural Language Processing (NLP) techniques or document classification. Familiarity with advanced machine learning architectures like transformers and convolutional networks. Experience with cloud platforms (GCP, AWS) and container-based development (Docker, Kubernetes). Ability to design, implement, and deploy system components, including regression and integration testing. 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/com-missioned roles) is expected to be ... (truncated, view full listing at source)