Sr. Machine Learning Engineer; DLP

Overview

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 challenging and disrupting the way things are done, and we’re looking for innovators who are as committed to shaping the future of cybersecurity as we are.

Who We Are
We take our mission of protecting the digital way of life seriously. We are relentless in protecting our customers and we believe that the unique ideas of every member of our team contributes to our collective success. Our values were crowdsourced by employees and are brought to life through each of us everyday - from disruptive innovation and collaboration, to execution.

From showing up for each other with integrity to creating an environment where we all feel included. As a member of our team, you will be shaping the future of cybersecurity. We work fast, value ongoing learning, and we respect each employee as a unique individual. Our development and personal wellbeing programs are designed to give you choice in how you are supported, including FLEX Benefits wellbeing spending account with over 1,000 eligible items, mental and financial health resources, and personalized learning opportunities.

At Palo Alto Networks, we believe in the power of collaboration and value in-person interactions. This is why our employees generally work full time from our office with flexibility offered where needed. This setup fosters casual conversations, problem-solving, and trusted relationships. Our goal is to create an environment where we all win with precision.

Your Career
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.

• 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

Your Experience

• 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
• Be an excellent programmer - experience with distributed cloud systems like GCP or AWS and containers like Docker a plus
• Proven track record in solving difficult real world problems by applying Machine Learning techniques
• Experience with deep learning frameworks such as PyTorch and Tensor Flow, Computer Vision, NLP, Large…