Principal Machine Learning Engineer (DLP)

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

The Team

Our engineering team is at the core of our products - connected directly to the mission of preventing cyberattacks. We are constantly innovating - challenging the way we, and the industry, think about cybersecurity. Our engineers don't shy away from building products to solve problems no one has pursued before. We define the industry, instead of waiting for directions. We need individuals who feel comfortable in ambiguity, excited by the prospect of a challenge, and empowered by the unknown risks facing our everyday lives that are only enabled by a secure digital environment.

Job Summary
Bring your machine learning and applied research expertise to build the next generation of cloud-delivered data security solutions. As a Machine Learning Engineer, you will work on large-scale ML systems that enable organizations to discover, classify, and protect highly sensitive data across SaaS applications. You will be part of a fast-paced, innovation-driven team that tackles complex real-world problems, develops novel algorithms, and deploys them into production at scale.

Our team operates at the intersection of ML research and production engineering, delivering customer-facing capabilities that directly impact data protection, compliance, and privacy. You will have the opportunity to work on cutting-edge ML, NLP, and Generative AI problems, contribute to patented technologies, and see your work deployed to millions of users.

This role is located at our dynamic Santa Clara California headquarters campus, and in office 3 days a week.

Job Responsibilities

• Apply machine learning, NLP, and deep learning methods to massive structured and unstructured data sets, classify documents, perform context analysis and extract complex patterns
• Leverage the latest advances in Deep Learning and NLP to develop scalable solutions to improve the overall product experience by ensuring high efficacy, low false positive and false negative rates
• Architect and end-to-end ownership of ML implementations while optimizing for scalability, performance and code quality
• Be a Technical Leader to develop and drive ML best practices and processes across the board
• Discover new opportunities to apply ML/NLP to solve critical problems and design a high-value roadmap that scales the impact of ML for customers
• Partner with Product and Business teams to ideate, collaborate and define product roadmaps that advance our ecosystem of Data Security and DLP offerings

• MS / PhD in Computer Science, Mathematics, Statistics, or related field or equivalent military experience required
• 7+ years industry / academia experience in software development, minimum 5 years as a machine learning engineer or a data scientist
• Proven track record in solving difficult real world problems by applying Machine Learning techniques
• Experience with deep learning frameworks such as PyTorch and TensorFlow, Computer Vision, NLP, Large Language Models, Generative AI or related areas is a big plus
• Strong working knowledge of machine learning algorithms such as XGBoost/CatBoost, CNNs, LSTMs, NLP frameworks like SpaCY, Gensim, NLTK, Byte Pair Encoding schemes, etc.
• Thorough understanding of ML Ops best practices, ability to design, test, measure algorithms/models and orchestrate and experience working with Airflow or Kubeflow
• Experience with time series analysis and anomaly detection techniques for identifying unusual patterns and potential security threats in data streams.
• Have a "get stuff done" attitude, enjoy being hands-on and working alongside the team to solve the most pressing problems in a fast-paced, collaborative environment

• Experience with distributed cloud systems like GCP or AWS and containers like Docker a plus
• Passion for security, prior experience in NLP and/or security products or services