Palo Alto Sr Staff Machine Learning Engineer DLP 

United States, California 

266800613

Being the cybersecurity partner of choice, protecting our digital way of life.

Your Career

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

Your Impact

• Develop AI-driven solutions: Apply state-of-the-art machine learning (ML), natural language processing (NLP), and deep learning techniques including LLMs to analyze vast structured and unstructured datasets, classify documents, extract insights, and detect nuanced patterns.
• Enhance AI accuracy & reliability: Leverage the latest advances in deep learning and NLP to build scalable models that optimize precision, minimize false positives/negatives, and improve the overall product experience.
• Lead end-to-end ML implementation: Architect and own machine learning pipelines, optimizing for scalability, efficiency, and maintainability while ensuring seamless integration with production systems.
• Drive ML innovation & best practices: Act as a technical leader, championing ML best practices, experimentation, and deployment strategies across teams.
• Identify high-impact opportunities: Discover novel ways to apply AI/ML for solving complex data security and privacy challenges, shaping a high-value roadmap that scales impact for customers.
• Collaborate with cross-functional teams: Partner with Product, Engineering, and Business teams to align ML advancements with strategic goals, driving innovation in Data Security and Data Loss Prevention (DLP) solutions.

Your Experience

• MS / PhD in Computer Science, Mathematics, Statistics, or a related field, or equivalent military experience.
• 5+ years of industry/academic experience in software development, with a minimum of 2 years as a machine learning engineer, data scientist, or LLM specialist .
• Strong programming skills with experience in distributed cloud systems (GCP, AWS, Azure) and containerization technologies like Docker and Kubernetes .
• Proven ability to solve real-world problems using machine learning, deep learning, and generative AI techniques .
• Experience with deep learning frameworks (PyTorch, TensorFlow), NLP models (transformers, BERT, GPT), Retrieval-Augmented Generation (RAG), and Large Language Models (LLMs) .
• Proficiency in ML algorithms such as XGBoost, CatBoost, CNNs, LSTMs , and NLP frameworks like spaCy, Gensim, NLTK, and tokenization techniques (Byte Pair Encoding, WordPiece, SentencePiece, etc.) .
• Strong understanding of ML Ops, model evaluation, fine-tuning, prompt engineering, and deployment best practices .
• Hands-on experience building and optimizing LLM-powered applications, vector search systems, and multimodal AI solutions .
• A “get stuff done” attitude, thriving in a fast-paced, collaborative environment while leading cutting-edge AI initiatives.
• Passion for security and AI-driven threat detection , with prior experience in NLP, cybersecurity, or data protection products a plus.

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.

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/commissioned roles) is expected to be between $160 - $190/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found .

All your information will be kept confidential according to EEO guidelines.