Senior Machine Learning Engineer (DLP)

Company Description

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 we’re looking for innovators who are as committed to shaping the future of cybersecurity as we are.

FLEXWORK is an employee-centric reimagining of how we work. We built FLEXWORK based on employee feedback – it is about flexibility, trust, and choice whenever possible. It’s been a journey of disruption that has yielded the best of our values. We offer as much flexibility as possible, and choices that enable you to be most productive, including benefits that meet your needs and learning opportunities that you feel passionate about.

This role is located at our Santa Clara, California headquarters campus.

Job Description

Your Career

We are looking for an exceptionally talented Machine Learning Engineer to be part of a fast paced team that uses Machine Learning to build innovative products for organizations to easily discover, classify, and protect highly sensitive data across SaaS applications. Our team finds solutions to hard problems, is innovative in finding data, builds models, and puts them into production. We produce several patents every year.

We expect office-based employees to be in the office four days per week, with one day working from where they choose. We believe being together facilitates casual conversations and those magic moments where we can work on issues and ideas informally. These moments build capability and deepen trusted relationships and allow our people to feel safe in taking risks and being disruptive. Like so many companies, we are working through the details and things could change …. but in general if a role is deemed office-based we want our teams to be together four days per week.

Your Impact

• 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
• Work with innovative co-workers 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

Qualifications

Your Experience

• MS / PhD in Computer Science, Mathematics, Statistics, or related field or equivalent military experience required
• 5+ years industry / academia experience in software development, minimum 2 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
• Enjoy 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
• Have a working knowledge of machine learning algorithms such as XGBoost/CatBoost, CNNs, LSTMs, NLP frameworks like SpaCY, Gensim, NLTK, Byte Pair Encoding schemes, etc.
• Understanding of ML Ops best practices, ability to design, test, measure algorithms/models and orchestrate
• 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
• Passion for security, prior experience in NLP and/or security products or services

Additional Information

The Team

To stay ahead of the curve, it’s critical to know where the curve is, and how to anticipate the changes we’re facing. For the fastest growing cybersecurity company, the curve is the evolution of cyberattacks, and the products and services that proactively address them. Our engineering team is at the core of our products – connected directly to the mission of preventing cyberattacks. They are constantly innovating – challenging the way we, and the industry, think about cybersecurity. These engineers aren’t shy about creating products to solve problems no one has tackled before. They define the industry, instead of waiting for directions. We need individuals who feel comfortable in ambiguity, excit